How Natural Language Processing Is Revolutionizing Business Operations
As a VP of Delivery at Intellias, Roman advises expertise to help businesses orchestrate their best products and services.
gettyThis year, all eyes will be on natural language processing (NLP). With OpenAI's GPT-4 and Meta's LLaMA out, the race for the best AI-powered NLP tech is officially on. So what hides behind the hype? What does NLP have to offer for global businesses? And do human workers have to worry about losing their jobs?
From my perspective, NLP technology is certainly going to revolutionize business operations and productivity. Here's why.
NLP and business operations are a perfect match.Today, many companies look closely at NLP solutions primarily based on the potential for cost savings. The technology has proven to be useful in saving resources such as time, money and human effort. For instance, IBM states that their NLP solutions can reduce time spent on information-gathering tasks by 50% (pg. 2).
Of course, how much NLP technology can save for a particular company will vary depending on the specific circumstances and context. In general, an NLP application can be useful in different areas of business operations, such as:
• Automating Routine Tasks: Take answering customer inquiries and processing transactions, for instance. An NLP solution can reduce the need for human involvement and save the company money on labor costs. According to Accenture, "40% of all working hours can be impacted by large language models (LLMs) like GPT-4."
• Structuring Company Data: An AI-powered NLP app can go through large volumes of text and analyze it on demand.
• Improving Customer Service And Supporting Efficiency: An NLP app can handle more customer inquiries in less time. It can improve the overall productivity of customer service teams.
• Improving Customer Satisfaction And Engagement: Thanks to high interactivity and 24/7 availability, research shows that LLMs could be useful in handling about 70% of complicated customer service communication (pg. 7).
• Conducting Dynamic Onboarding And Training: NLP solutions can train workers in an efficient and interactive way.
• Reducing Human Errors: NLP can save money by providing accurate and consistent responses and therefore reduce the need for costly corrections and rework.
Let's take a look at one of the possible applications of NLP. Recently, at my company, we built a conversational virtual teaching assistant for a global car manufacturer. The NLP app helps sales teams strengthen their product knowledge.
The chatbot understands questions and provides instant replies. The bot can also show a video, a photograph or a slide deck. Through this interactive training, a salesperson learns how to quickly and accurately consult customers on any questions about the product.
Here is the roadmap for successful NLP bot cooperation.Let's take ChatGPT, for example. Here's how to use it properly for business operations.
1. Define your business goals before the implementation. This will help you choose the right provider and solution that align with your business objectives.
2. Choose a reputable provider that has a track record of successful ChatGPT deployments and can provide references with case studies.
3. Evaluate the solution's capabilities to ensure it can handle your business needs. Consider factors such as the solution's accuracy, speed, scalability and customization options.
4. Plan for deployment and maintenance. Make sure you have a plan for integrating the solution into your existing systems, training your team on how to use it and providing ongoing support and maintenance.
5. Test ChatGPT before deployment with a small group of customers or employees to identify any issues or bugs.
6. Constantly train ChatGPT to improve its performance and accuracy.
7. Address ethical considerations, such as potential bias in training data or lack of transparency.
8. Ensure data privacy and security to protect your customers' personal information and your business reputation.
9. Continuously monitor and evaluate the performance of ChatGPT to ensure it's meeting your business goals. Use performance metrics such as accuracy, response time and customer satisfaction to evaluate the solution's effectiveness.
10. Improve and innovate with ChatGPT to stay ahead of the competition. Explore new use cases and applications, and consider integrating new technologies.
The human touch is still important.Despite the increasing sophistication of NLP solutions, there are situations in which human contact will remain equally important. For example, NLP solutions may not be able to provide accurate emotional support to customers who are upset or distressed. Sure, the technology can detect the emotion or intent behind a customer's text (i.E., perform sentiment analysis). But the response an NLP app generates can't yet compare in empathy to personal human contact.
In addition, certain situations are generally better suited to human workers, such as creative problem-solving and decision making. Judging from my experience, NLP technology can handle routine tasks and provide basic information really well. But it's not yet advanced enough to fully replace human workers' critical thinking.
So, no worries, NLP tech won't completely replace human interaction, expertise and experience—at least in the near future. Instead, for now, NLP technology can accompany human workers and assist them with certain tasks.
Beware: The future is here.Everyone knows it; advanced NLP solutions are here to stay. They've already proven to be useful and worthy of investment. NLP apps help reduce the costs of conducting business operations. In addition, they drive customer satisfaction and grow revenue. It's no wonder that today, businesses go after NLP so obsessively.
Now, companies are in a position where the technology adoption becomes not just a small internal operations improvement but a matter of survival—because there's always a risk of getting overrun by your competitors.
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Global Natural Language Processing (NLP) In Healthcare And Life Sciences Market To Reach $11.5 Billion By 2030
ReportLinker
The global economy is at a critical crossroads with a number of interlocking challenges and crises running in parallel. The uncertainty around how Russia`s war on Ukraine will play out this year and the war`s role in creating global instability means that the trouble on the inflation front is not over yet.
New York, May 17, 2023 (GLOBE NEWSWIRE) -- Reportlinker.Com announces the release of the report "Global Natural Language Processing (NLP) in Healthcare and Life Sciences Industry" - https://www.Reportlinker.Com/p06032314/?Utm_source=GNWFood and fuel inflation will remain a persistent economic problem. Higher retail inflation will impact consumer confidence and spending. As governments combat inflation by raising interest rates, new job creation will slowdown and impact economic activity and growth. Lower capital expenditure is in the offing as companies go slow on investments, held back by inflation worries and weaker demand. With slower growth and high inflation, developed markets seem primed to enter into a recession. Fears of new COVID outbreaks and China's already uncertain post-pandemic path poses a real risk of the world experiencing more acute supply chain pain and manufacturing disruptions this year. Volatile financial markets, growing trade tensions, stricter regulatory environment and pressure to mainstream climate change into economic decisions will compound the complexity of challenges faced. Year 2023 is expected to be tough year for most markets, investors and consumers. Nevertheless, there is always opportunity for businesses and their leaders who can chart a path forward with resilience and adaptability.
Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market to Reach $11.5 Billion by 2030
In the changed post COVID-19 business landscape, the global market for Natural Language Processing (NLP) in Healthcare and Life Sciences estimated at US$3.1 Billion in the year 2022, is projected to reach a revised size of US$11.5 Billion by 2030, growing at aCAGR of 18% over the period 2022-2030. Solutions, one of the segments analyzed in the report, is projected to record 14.4% CAGR and reach US$5.6 Billion by the end of the analysis period. Taking into account the ongoing post pandemic recovery, growth in the Services segment is readjusted to a revised 22.6% CAGR for the next 8-year period.
The U.S. Market is Estimated at $823.2 Million, While China is Forecast to Grow at 23.9% CAGR
The Natural Language Processing (NLP) in Healthcare and Life Sciences market in the U.S. Is estimated at US$823.2 Million in the year 2022. China, the world`s second largest economy, is forecast to reach a projected market size of US$3 Billion by the year 2030 trailing a CAGR of 23.9% over the analysis period 2022 to 2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 11.4% and 15.1% respectively over the 2022-2030 period. Within Europe, Germany is forecast to grow at approximately 12.9% CAGR.
Select Competitors (Total 33 Featured)- 3M- Amazon Web Services Inc.- Apixio Inc.- Averbis- Cerner Corporation- Clinithink- Conversica Inc.- Dolby Systems Inc.- Google LLC- Health Fidelty Inc.- IBM- Inovalon- Lexlytics- Linguamantics- Microsoft- Narrative Science- Nuance Communications Inc.- Sparkcognition- Stats LLC- Wave Health Technologies
Read the full report: https://www.Reportlinker.Com/p06032314/?Utm_source=GNW
I. METHODOLOGY
II. EXECUTIVE SUMMARY
1. MARKET OVERVIEWImpact of Covid-19 and a Looming Global RecessionNatural Language Processing (NLP) in Healthcare and LifeSciences - Global Key Competitors Percentage Market Share in2022 (E)Competitive Market Presence - Strong/Active/Niche/Trivial forPlayers Worldwide in 2022 (E)
2. FOCUS ON SELECT PLAYERS
3. MARKET TRENDS & DRIVERS
4. GLOBAL MARKET PERSPECTIVETable 1: World Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific, Latin America, Middle East and AfricaMarkets - Independent Analysis of Annual Sales in US$ Thousandfor Years 2022 through 2030 and % CAGR
Table 2: World 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa Markets for Years 2023 & 2030
Table 3: World Recent Past, Current & Future Analysis forSolutions by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific, Latin America, Middle East and AfricaMarkets - Independent Analysis of Annual Sales in US$ Thousandfor Years 2022 through 2030 and % CAGR
Table 4: World 8-Year Perspective for Solutions by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa for Years 2023 & 2030
Table 5: World Recent Past, Current & Future Analysis forServices by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific, Latin America, Middle East and AfricaMarkets - Independent Analysis of Annual Sales in US$ Thousandfor Years 2022 through 2030 and % CAGR
Table 6: World 8-Year Perspective for Services by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa for Years 2023 & 2030
Table 7: World Recent Past, Current & Future Analysis for OtherApplications by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific, Latin America, Middle East and AfricaMarkets - Independent Analysis of Annual Sales in US$ Thousandfor Years 2022 through 2030 and % CAGR
Table 8: World 8-Year Perspective for Other Applications byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific, Latin America,Middle East and Africa for Years 2023 & 2030
Table 9: World Recent Past, Current & Future Analysis for Text &Speech Analytics by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific, Latin America, Middle East andAfrica Markets - Independent Analysis of Annual Sales in US$Thousand for Years 2022 through 2030 and % CAGR
Table 10: World 8-Year Perspective for Text & Speech Analyticsby Geographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific, Latin America,Middle East and Africa for Years 2023 & 2030
Table 11: World Recent Past, Current & Future Analysis forInteractive Voice Response by Geographic Region - USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa Markets - Independent Analysis of Annual Sales inUS$ Thousand for Years 2022 through 2030 and % CAGR
Table 12: World 8-Year Perspective for Interactive VoiceResponse by Geographic Region - Percentage Breakdown of ValueSales for USA, Canada, Japan, China, Europe, Asia-Pacific,Latin America, Middle East and Africa for Years 2023 & 2030
Table 13: World Recent Past, Current & Future Analysis forPattern & Image Recognition by Geographic Region - USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa Markets - Independent Analysis of Annual Sales inUS$ Thousand for Years 2022 through 2030 and % CAGR
Table 14: World 8-Year Perspective for Pattern & ImageRecognition by Geographic Region - Percentage Breakdown ofValue Sales for USA, Canada, Japan, China, Europe,Asia-Pacific, Latin America, Middle East and Africa for Years2023 & 2030
Table 15: World Recent Past, Current & Future Analysis for AutoCoding by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific, Latin America, Middle East and AfricaMarkets - Independent Analysis of Annual Sales in US$ Thousandfor Years 2022 through 2030 and % CAGR
Table 16: World 8-Year Perspective for Auto Coding byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific, Latin America,Middle East and Africa for Years 2023 & 2030
Table 17: World Recent Past, Current & Future Analysis forClassification & Categorization by Geographic Region - USA,Canada, Japan, China, Europe, Asia-Pacific, Latin America,Middle East and Africa Markets - Independent Analysis of AnnualSales in US$ Thousand for Years 2022 through 2030 and % CAGR
Table 18: World 8-Year Perspective for Classification &Categorization by Geographic Region - Percentage Breakdown ofValue Sales for USA, Canada, Japan, China, Europe,Asia-Pacific, Latin America, Middle East and Africa for Years2023 & 2030
Table 19: World Recent Past, Current & Future Analysis forCloud by Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific, Latin America, Middle East and Africa Markets -Independent Analysis of Annual Sales in US$ Thousand for Years2022 through 2030 and % CAGR
Table 20: World 8-Year Perspective for Cloud by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa for Years 2023 & 2030
Table 21: World Recent Past, Current & Future Analysis forOn-Premise by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific, Latin America, Middle East and AfricaMarkets - Independent Analysis of Annual Sales in US$ Thousandfor Years 2022 through 2030 and % CAGR
Table 22: World 8-Year Perspective for On-Premise by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific, Latin America, Middle Eastand Africa for Years 2023 & 2030
Table 23: World Natural Language Processing (NLP) in Healthcareand Life Sciences Market Analysis of Annual Sales in US$Thousand for Years 2014 through 2030
III. MARKET ANALYSIS
UNITED STATESNatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in the United States for 2023 (E)Table 24: USA Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 25: USA 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 26: USA Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 27: USA 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 28: USA Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 29: USA 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
CANADATable 30: Canada Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 31: Canada 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 32: Canada Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 33: Canada 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 34: Canada Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 35: Canada 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
JAPANNatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in Japan for 2023 (E)Table 36: Japan Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 37: Japan 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 38: Japan Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 39: Japan 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 40: Japan Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 41: Japan 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
CHINANatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in China for 2023 (E)Table 42: China Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 43: China 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 44: China Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 45: China 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 46: China Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 47: China 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
EUROPENatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in Europe for 2023 (E)Table 48: Europe Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Geographic Region - France, Germany, Italy, UK,Spain, Russia and Rest of Europe Markets - Independent Analysisof Annual Sales in US$ Thousand for Years 2022 through 2030 and% CAGR
Table 49: Europe 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by GeographicRegion - Percentage Breakdown of Value Sales for France,Germany, Italy, UK, Spain, Russia and Rest of Europe Marketsfor Years 2023 & 2030
Table 50: Europe Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 51: Europe 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 52: Europe Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 53: Europe 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 54: Europe Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 55: Europe 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
FRANCENatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in France for 2023 (E)Table 56: France Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 57: France 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 58: France Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 59: France 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 60: France Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 61: France 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
GERMANYNatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in Germany for 2023 (E)Table 62: Germany Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 63: Germany 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 64: Germany Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 65: Germany 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 66: Germany Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 67: Germany 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
ITALYTable 68: Italy Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 69: Italy 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 70: Italy Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 71: Italy 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 72: Italy Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 73: Italy 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
UNITED KINGDOMNatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in the United Kingdom for 2023 (E)Table 74: UK Recent Past, Current & Future Analysis for NaturalLanguage Processing (NLP) in Healthcare and Life Sciences byComponent - Solutions and Services - Independent Analysis ofAnnual Sales in US$ Thousand for the Years 2022 through 2030and % CAGR
Table 75: UK 8-Year Perspective for Natural Language Processing(NLP) in Healthcare and Life Sciences by Component - PercentageBreakdown of Value Sales for Solutions and Services for theYears 2023 & 2030
Table 76: UK Recent Past, Current & Future Analysis for NaturalLanguage Processing (NLP) in Healthcare and Life Sciences byApplication - Other Applications, Text & Speech Analytics,Interactive Voice Response, Pattern & Image Recognition, AutoCoding and Classification & Categorization - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 77: UK 8-Year Perspective for Natural Language Processing(NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 78: UK Recent Past, Current & Future Analysis for NaturalLanguage Processing (NLP) in Healthcare and Life Sciences byDeployment - Cloud and On-Premise - Independent Analysis ofAnnual Sales in US$ Thousand for the Years 2022 through 2030and % CAGR
Table 79: UK 8-Year Perspective for Natural Language Processing(NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
SPAINTable 80: Spain Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 81: Spain 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 82: Spain Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 83: Spain 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 84: Spain Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 85: Spain 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
RUSSIATable 86: Russia Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 87: Russia 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 88: Russia Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 89: Russia 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 90: Russia Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 91: Russia 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
REST OF EUROPETable 92: Rest of Europe Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 93: Rest of Europe 8-Year Perspective for NaturalLanguage Processing (NLP) in Healthcare and Life Sciences byComponent - Percentage Breakdown of Value Sales for Solutionsand Services for the Years 2023 & 2030
Table 94: Rest of Europe Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 95: Rest of Europe 8-Year Perspective for NaturalLanguage Processing (NLP) in Healthcare and Life Sciences byApplication - Percentage Breakdown of Value Sales for OtherApplications, Text & Speech Analytics, Interactive VoiceResponse, Pattern & Image Recognition, Auto Coding andClassification & Categorization for the Years 2023 & 2030
Table 96: Rest of Europe Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 97: Rest of Europe 8-Year Perspective for NaturalLanguage Processing (NLP) in Healthcare and Life Sciences byDeployment - Percentage Breakdown of Value Sales for Cloud andOn-Premise for the Years 2023 & 2030
ASIA-PACIFICNatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in Asia-Pacific for 2023 (E)Table 98: Asia-Pacific Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Geographic Region - Australia, India, South Koreaand Rest of Asia-Pacific Markets - Independent Analysis ofAnnual Sales in US$ Thousand for Years 2022 through 2030 and %CAGR
Table 99: Asia-Pacific 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by GeographicRegion - Percentage Breakdown of Value Sales for Australia,India, South Korea and Rest of Asia-Pacific Markets for Years2023 & 2030
Table 100: Asia-Pacific Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 101: Asia-Pacific 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 102: Asia-Pacific Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & SpeechAnalytics, Interactive Voice Response, Pattern & ImageRecognition, Auto Coding and Classification & Categorization -Independent Analysis of Annual Sales in US$ Thousand for theYears 2022 through 2030 and % CAGR
Table 103: Asia-Pacific 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Application -Percentage Breakdown of Value Sales for Other Applications,Text & Speech Analytics, Interactive Voice Response, Pattern &Image Recognition, Auto Coding and Classification &Categorization for the Years 2023 & 2030
Table 104: Asia-Pacific Recent Past, Current & Future Analysisfor Natural Language Processing (NLP) in Healthcare and LifeSciences by Deployment - Cloud and On-Premise - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 105: Asia-Pacific 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Deployment -Percentage Breakdown of Value Sales for Cloud and On-Premisefor the Years 2023 & 2030
AUSTRALIANatural Language Processing (NLP) in Healthcare and LifeSciences Market Presence - Strong/Active/Niche/Trivial - KeyCompetitors in Australia for 2023 (E)Table 106: Australia Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Component - Solutions and Services - IndependentAnalysis of Annual Sales in US$ Thousand for the Years 2022through 2030 and % CAGR
Table 107: Australia 8-Year Perspective for Natural LanguageProcessing (NLP) in Healthcare and Life Sciences by Component -Percentage Breakdown of Value Sales for Solutions and Servicesfor the Years 2023 & 2030
Table 108: Australia Recent Past, Current & Future Analysis forNatural Language Processing (NLP) in Healthcare and LifeSciences by Application - Other Applications, Text & Speech
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CONTACT: Clare: [email protected] US: (339)-368-6001 Intl: +1 339-368-60015 Real-world Applications Of Natural Language Processing (NLP)
Natural language processing (NLP) is a field of study that focuses on enabling computers to understand and interpret human language. NLP involves applying machine learning algorithms to analyze and process natural language data, such as text or speech.
NLP has recently been incorporated into a number of practical applications, including sentiment analysis, chatbots and speech recognition. NLP is being used by businesses in a wide range of sectors to automate customer care systems, increase marketing initiatives and improve product offers.
Related: 5 natural language processing (NLP) libraries to use
Specifically, this article looks at sentiment analysis, chatbots, machine translation, text summarization and speech recognition as five instances of NLP in use in the real world. These applications have the potential to revolutionize the way one communicates with technology, making it more natural, intuitive and user-friendly.
Sentiment analysisNLP can be used to analyze text data to determine the sentiment of the writer toward a particular product, service or brand. This is used in applications such as social media monitoring, customer feedback analysis and market research.
A common use of NLP is sentiment analysis of the stock market, in which investors and traders examine social media sentiment on a particular stock or market. An investor, for instance, can use NLP to examine tweets or news stories about a specific stock to ascertain the general attitude of the market toward that stock. Investors can determine whether these sources are expressing positive or negative opinions about the stock by studying the terminology used in these sources.
By supplying information on market sentiment and enabling investors to modify their strategies as necessary, sentiment research can assist investors in making more educated investment decisions. For instance, if a stock is receiving a lot of positive sentiment, an investor may consider buying more shares, while negative sentiment may prompt them to sell or hold off on buying.
ChatbotsNLP can be used to build conversational interfaces for chatbots that can understand and respond to natural language queries. This is used in customer support systems, virtual assistants and other applications where human-like interaction is required.
A chatbot like ChatGPT that can help consumers with their account questions, transaction histories and other financial questions might be created by a financial institution using NLP. Customers can easily obtain the information they require thanks to the chatbot's ability to comprehend and respond to natural language questions.
Machine translationNLP can be used to translate text from one language to another. This is used in applications such as Google Translate, Skype Translator and other language translation services.
Similarly, a multinational corporation may use NLP to translate product descriptions and marketing materials from their original language to the languages of their target markets. This allows them to communicate more effectively with customers in different regions.
Text summarizationNLP can be used to summarize long documents and articles into shorter, concise versions. This is used in applications such as news aggregation services, research paper summaries and other content curation services.
NLP can be used by a news aggregator to condense lengthy news stories into shorter, easier-to-read versions. Without having to read the entire article, readers can immediately receive a summary of the news thanks to text summarization.
Related: 7 artificial intelligence (AI) examples in everyday life
Speech recognitionNLP can be used to convert spoken language into text, allowing for voice-based interfaces and dictation. This is used in applications such as virtual assistants, speech-to-text transcription services and other voice-based applications.
A virtual assistant, such as Alexa from Amazon or Assistant from Google, uses NLP to comprehend spoken instructions and answer questions in natural language. Instead of having to type out commands or inquiries, users may now converse with the assistant by speaking.
