What Is NLP? Natural Language Processing Explained
Natural language processing is a branch of AI that enables computers to understand, process, and generate language just as people do — and its use in business is rapidly growing.
Natural language processing definitionNatural language processing (NLP) is the branch of artificial intelligence (AI) that deals with training computers to understand, process, and generate language. Search engines, machine translation services, and voice assistants are all
While the term originally referred to a system's ability to read, it's since become a colloquialism for all computational linguistics. Subcategories include natural language generation (NLG) — a computer's ability to create communication of its own — and natural language understanding (NLU) — the ability to understand slang, mispronunciations, misspellings, and other variants in language.
The introduction of transformer models in the 2017 paper "Attention Is All You Need" by Google researchers revolutionized NLP, leading to the creation of generative AI models such as Bidirectional Encoder Representations from Transformer (BERT) and subsequent DistilBERT — a smaller, faster, and more efficient BERT — Generative Pre-trained Transformer (GPT), and Google Bard.
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How natural language processing worksNLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Phrases, sentences, and sometimes entire books are fed into ML engines where they're processed using grammatical rules, people's real-life linguistic habits, and the like. An NLP algorithm uses this data to find patterns and extrapolate what comes next. For example, a translation algorithm that recognizes that, in French, "I'm going to the park" is "Je vais au parc" will learn to predict that "I'm going to the store" also begins with "Je vais au." All the algorithm then needs is the word for "store" to complete the translation task.
NLP applicationsMachine translation is a powerful NLP application, but search is the most used. Every time you look something up in Google or Bing, you're helping to train the system. When you click on a search result, the system interprets it as confirmation that the results it has found are correct and uses this information to improve search results in the future.
Chatbots work the same way. They integrate with Slack, Microsoft Messenger, and other chat programs where they read the language you use, then turn on when you type in a trigger phrase. Voice assistants such as Siri and Alexa also kick into gear when they hear phrases like "Hey, Alexa." That's why critics say these programs are always listening; if they weren't, they'd never know when you need them. Unless you turn an app on manually, NLP programs must operate in the background, waiting for that phrase.
Transformer models take applications such as language translation and chatbots to a new level. Innovations such as the self-attention mechanism and multi-head attention enable these models to better weigh the importance of various parts of the input, and to process those parts in parallel rather than sequentially.
Rajeswaran V, senior director at Capgemini, notes that Open AI's GPT-3 model has mastered language without using any labeled data. By relying on morphology — the study of words, how they are formed, and their relationship to other words in the same language — GPT-3 can perform language translation much better than existing state-of-the-art models, he says.
NLP systems that rely on transformer models are especially strong at NLG.
Natural language processing examplesData comes in many forms, but the largest untapped pool of data consists of text — and unstructured text in particular. Patents, product specifications, academic publications, market research, news, not to mention social media feeds, all have text as a primary component and the volume of text is constantly growing. Apply the technology to voice and the pool gets even larger. Here are three examples of how organizations are putting the technology to work:
Whether you're building a chatbot, voice assistant, predictive text application, or other application with NLP at its core, you'll need tools to help you do it. According to Technology Evaluation Centers, the most popular software includes:
There's a wide variety of resources available for learning to create and maintain NLP applications, many of which are free. They include:
Here are some of the most popular job titles related to NLP and the average salary (in US$) for each position, according to data from PayScale.
Natural Language Processing (Nlp) In Healthcare And Life Sciences Market Analysis 2023-2029 X Herald
(MENAFN- Ameliorate Digital Consultancy)The natural language processing (nlp) in healthcare and life sciences Market research report provides all the information related to the industry. It gives the markets outlook by giving authentic data to its client which helps to make essential decisions. It gives an overview of the market which includes its definition, applications and developments, and manufacturing technology. This natural language processing (nlp) in healthcare and life sciences market research report tracks all the recent developments and innovations in the market. It gives the data regarding the obstacles while establishing the business and guides to overcome the upcoming challenges and obstacles.
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Key Players in This Report Include:
electronic health records (ehr), computer-assisted coding (cac), clinician document, others
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natural language processing (nlp) in healthcare and life sciences Market Segments by Type:
Machine TranslationInformation ExtractionAutomatic SummarizationText and Voice ProcessingOthers
natural language processing (nlp) in healthcare and life sciences Market Segments by Application:
Electronic Health Records (EHR)Computer-Assisted Coding (CAC)Clinician DocumentOthers
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North American market (United States, Canada, North America, Mexico),European market (Germany, France, United Kingdom, Russia, Italy),
Asia-Pacific market (China, Japan, Korea, Asian countries, India, Southeast Asia),South American market (Brazil, Argentina) , Colombia, etc.),Middle East and African markets (Saudi Peninsula, United Arab Emirates, Egypt, Nigeria, South Africa)
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Chapter 2: Global Economic Impact on Industry
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COTA Wins Google Cloud Customer Of The Year Award For Using AI To Improve Cancer Care
NEW YORK, Aug. 29, 2023 /PRNewswire/ -- COTA today announced that it has received both the 2023 Google Cloud Customer of the Year Award and the Diversity, Equity, and Inclusion Award for its work using AI to accelerate the abstraction, validation and use of real-world data, sourced from electronic health records, to bring clarity to cancer care.
COTA was recognized for its achievements in the Google Cloud ecosystem and is building a series of new AI and natural language processing (NLP) models tailored to unstructured oncology data. The ultimate goal of this work is to ensure that all patients receive high-quality care regardless of who they are or where they live. These models will help COTA and its customers achieve faster, easier and better understanding of what is happening in the cancer care setting and how a patient's clinical history may impact their response to treatment.
"Real-world data is key to unlocking insights that can improve individual patient outcomes across the entire healthcare ecosystem. With AI, we can dramatically accelerate the process of creating high-quality data responsibly so that we can uncover disparities and improve cancer treatment," Miruna Sasu, President and CEO, COTA. "Our partnership with Google Cloud is vital in helping advance this important work."
"The Google Cloud Customer Awards are an opportunity to recognize the most innovative, technically advanced, and transformative cloud deployments across industries, from around the globe, built on our platform," said Brian Hall, VP of Product and Industry Marketing at Google Cloud. "I want to congratulate COTA on achieving this award and serving as an innovator for the industry."
The electronic health record (EHR) has revolutionized the way healthcare providers capture data, but challenges remain in transforming raw, unstructured health data into a usable format. COTA is tackling this challenge head-on, with the goal of fueling a new era of data-driven cancer care.
COTA augments manual, human-led data abstraction with technology-first abstraction and curation best practices - and in some cases, eliminates human intervention completely. This approach provides access to even more advanced data elements that may be buried in unstructured clinical notes. For example, next-generation genomic sequencing is becoming particularly important for personalizing cancer care. The reports providers receive from the genetic testing labs are often in a PDF format that traditional tools like optical character recognition (OCR) can't accurately "read", so this data often goes unused today.
COTA programmatically ingests data, then it is cleaned and mapped against control data to standardize the ontologies like regimens, histology, labs, and demographics. Using NLP and semi-structured data mining for a select number of data elements like molecular markers, adverse events, and comorbidities, COTA is speeding up the process and making it more efficient.
About COTA, Inc.
Founded by oncologists, COTA is committed to creating a precise, patient-first approach to cancer care through the use of real-world data. The company leverages technology-supported data abstraction methods to make sense of complex, fragmented patient data from the real world. Offering the highest quality oncology real-world data from leading academic and community-based cancer centers and an advanced analytics platform, COTA partners with leading life sciences companies, providers, and payers to ensure that everyone touched by cancer has a clear path to the right care. To learn more about COTA and how to fast-track improvements in cancer care and treatment with comprehensive and diverse real-world data and analytics, visit cotahealthcare.Com.
CONTACT: Jaimee Ryan, [email protected]
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