Imagine it's the year 2040. You wake up from your sleep. Your digital health assistant runs a thorough diagnosis of your body in thirty seconds, deploying dozens of sensors and collecting gigabytes of data. It indicates that you may have the flu based on the previous 48 hours. How near are we to making this a reality? Artificial Intelligence (AI) is a machine’s ability to analyse data, identify patterns, and predict future outcomes using its own intelligence. It’s like teaching a machine basic math and then seeing it learn calculus. 

So how does this affect healthcare? It envisions an AI that learns your preferences, anticipates your wants and activities, monitors your health, and assists you in problem-solving in support of your health. However, for AI to produce accurate results, it requires data to learn an algorithm to work with. It is now up to your Medical AI to use that medical datasets to shift medicine away from retrospective, reactive, and generic… and toward prospective, proactive and personalised. Today, we’ll look at the role of AI in the future of healthcare from two lenses, personalized and precision medicine, and medical interventions. 

Medicine with precision and personalization

Going to the doctor nowadays is more about sick care than healthcare. It is reactive rather than proactive. Typically, you seek or receive medical assistance only after being ill. Diagnostic medicine advancements are important to transforming sick care into genuine healthcare- in other words, using technology to keep you healthy. 

Let’s take a look at five ways AI is influencing precision and personalised medicine. 

1. How does AI make use of data collected by wearables and health monitoring sensors? AI and health monitoring wearables go hand in hand. Take, for example, the Oura Ring, one of the most promising wellness rings. The Rockefeller Neuroscience institute has collaborated with Oura to create an AI-driven model for identifying the people who are contagious with the flu. And the findings of their first investigation were encouraging. The Oura ring, with its infrared LEDs, accelerometer, gyroscopes, and body temperature sensors, was able to detect common covid-19 symptoms three days earlier with 90% accuracy.

2. How does Artificial Intelligence Improve point of care diagnostics such as ultrasounds? Exo has created a device that combines ultrasound and artificial intelligence to improve patient imaging. It doesn’t simply utilise cutting-edge sensors and nanotechnologies to visualise any region of the body- organs and vasculature- and convert it into a 3D image. It employs a revolutionary computational photography method to provide real-time procedural advice.

In other words, it enables clinicians to parse clinical findings using ultrasonography in real-time. These diagnostics will broaden medicine’s reach by making previously skill-based treatments more accessible to a less trained users. 

3. Can artificial intelligence improve the efficiency and accuracy of medical imaging analysis? Qure.ai is one of the most advanced startups using AI-powered medical imaging technologies. They have specialised algorithms for x-rays, CT scans, and MRIs, which are the three most often utilised imaging modalities in hospitals. Their products include fully automated detection as well as a 3D visualisation. Their algorithms are also extremely accurate. 

4. How might artificial intelligence help with cancer detection and treatment? How does a doctor tell the difference between cancer stages and whether to perform surgery to chemotherapy? They take a biopsy of the cancer tissue, examine it under a microscope, and then make a diagnosis. PathAI supports pathologists in making an accurate and timely diagnosis for every patient, every time. 

5. What if we could use AI to accelerate drug discovery? Insilico Medicine is an AI-powered platform that assists in the identification of novel therapeutic targets, the fast testing of drug candidates, and the selection of those suitable for further development. Its “drug discovery engine” shifts through millions of datasets to identify the biological signatures of certain diseases. It detects the most potential therapeutic targets and produces molecules that are exactly suited to them using generative adversarial networks (GAN), a new AI technology.  

AI and Medical Data

As healthcare datasets continue to rise exponentially, a mortal physician’s ability to keep up and process all of the accessible data has become impractical. The unassisted MD vanished in the digital dust a long time ago. 

Consider going to a place which may include a full-body MRI, Coronary CT, full-genome sequence, blood tests, and much more. A checkup of this nature creates more than 150 gigabytes of data about you, your body, and your health. What would a doctor from just 20 years ago do with all of this data? It is pointless without AI, right? What about the flood of medical research that is being published? Did you know that a new medical article is published every 26 seconds? That’s 3,300 articles per day or more than 1.2 million per year. What percentage of these articles has your doctor reads? The AI doctor/physician can read them all. Even better, it has the ability to consume every medical article ever written. 

AI and medical procedures

Now that we’ve covered precision and personalised medicine. What if your illness isn’t treatable with medicines, and necessitates surgery? According to a study conducted at Baylor Medical Center, despite the best training, more than half of unfavourable surgical outcomes are caused by human error. In the surgical context, the adage, “to err is human” could mean the difference between life and death. This is why there is a desire for minimally invasive techniques. There is less risk because humans are required to do less. It’s not an attack on medical education; it’s just the way things are. 

This is where the soft tissue autonomous robot (STAR) comes in: a robot that can suture tissue five to ten times faster and with higher precision than a human. It has fluorescence and 3D imaging, force sensing, and submillimeter positioning, in addition to cutting and suturing. It was demonstrated that it could suture together two segments of the intestine better than professional surgeons. In animal studies, it was also able to use a precise map of a typical heart plus input from built-in touch and visual sensors to detect the damaged valve location with 95% accuracy. 

This isn’t AI taking the place of the surgeon. It’s employing AI for technical skill augmentation, in which it employs algorithms to match or outperform human surgeons over time based on its expertise with procedures- sort of like residency, but for robots. Following that, it will attempt to master more difficult surgeries such as cancerous tumour removal, trauma surgery, and heart surgery. 

With advancements like this, procedures will no longer be as risky. 

How GTS can help you?

AI has already transformed medicine by analysing enormous amounts of data to identify patterns and insights that can save lives. The explosion of data at our fingertips is by far today’s biggest fuel source for AI development. At the same time, we are rapidly consuming that data and developing machine learning algorithms to filter through it, detect patterns, and apply it forward. And that’s why we at Global Technology Solutions understand your need for healthcare datasets for machine learning. Our services includes data annotation and data collection services to match your needs.