AI in Healthcare. Transformational.

The emergence of artificial intelligence (AI) in healthcare has been groundbreaking, reshaping the way patients are diagnosed, treated and monitored.

Experts are clear this technology is drastically improving healthcare research and outcomes by producing more accurate diagnoses and enabling more personalized treatments. AI offers healthcare the ability to analyze vast amounts of clinical documentation quickly, helping medical professionals identify disease markers and trends that would otherwise be overlooked. The potential applications of AI and healthcare are broad and far-reaching, from scanning radiological images for early detection to predicting outcomes from electronic health records

AI has transformed medical coding too, by automating the coding process, minimizing errors, and significantly improving efficiency.

AI-powered coding tools use natural language processing (NLP) and machine learning algorithms to analyze medical records, identify relevant codes, and assign them automatically. The benefits of AI in medical coding are numerous. Firstly, AI coding tools can reduce the error rate of medical coding, ensuring accurate and consistent documentation. Secondly, AI coding tools can reduce the time and cost of medical coding, enabling healthcare providers to allocate resources more efficiently. Thirdly, AI coding tools can improve patient outcomes by identifying trends and patterns in medical data, enabling early detection and intervention.

AnnoVelocity is brought to you by Annova , we are that Human in the Loop who make AI more intelligent with an annotation accuracy of 99.9% . We work across industries and our algorithm for a sports analytics client has been covered in The New York Times. We leverage AI across our entire work spectrum, including Medical Coding, where we have a significant play with the ability to scale if the project demands.

Introducing Exscientia, who practices Patient First AI.


This is one of the game - changer companies who actively apply AI to precision engineer medicines more rapidly and efficiently, enabling people to live more healthy and productive lives. Here’s one of their breakthrough stories.

At 82 years old, with an aggressive form of blood cancer that six courses of chemotherapy had failed to eliminate, “Paul”, ( not his real name) appeared to be out of options. With each long and unpleasant round of treatment, his doctors had been working their way down a list of common cancer drugs, hoping to hit on something that would prove effective—and crossing them off one by one. The usual cancer killers were not doing their job.

With nothing to lose, Paul’s doctors enrolled him in a trial set up by the Medical University of Vienna in Austria, where he lives. The university was testing a new matchmaking technology developed by Exscientia that pairs individual patients with the precise drugs they need, taking into account the subtle biological differences between people.

The researchers took a small sample of tissue from Paul. They divided the sample, which included both normal cells and cancer cells, into more than a hundred pieces and exposed them to various cocktails of drugs. Then, using robotic automation and computer vision (machine-learning models trained to identify small changes in cells), they watched to see what would happen.

In effect, the researchers were doing what the doctors had done: trying different drugs to see what worked. But instead of putting a patient through multiple months-long courses of chemotherapy, they were testing dozens of treatments all at the same time.

The approach allowed the team to carry out an exhaustive search for the right drug. Some of the medicines didn’t kill Paul’s cancer cells. Others harmed his healthy cells. Paul was too frail to take the drug that came out on top. So he was given the runner-up in the matchmaking process: a cancer drug marketed by the pharma giant Johnson & Johnson that Paul’s doctors had not tried because previous trials had suggested it was not effective at treating his type of cancer.

It worked. Two years on, Paul was in complete remission—his cancer was gone. The approach is a big change for the treatment of cancer, says Exscientia’s CEO, Andrew Hopkins: “The technology we have to test drugs in the clinic really does translate to real patients.

AI is on the cusp of many more such triumphs.

Buoy. The symptom checking chatbot.


The age of chatbots in healthcare might have arrived earlier, but now, they are taking real charge.

The days of Googling for cures and probably even ending up worse are a thing of the past.

Your situation is specific to you says Buoy who asks questions and helps narrow down what is going on based on your answers. No more guessing and filling in the blanks. It's like talking to your friend who happens to be a doctor.

Reportedly developed by a team of doctors and computer scientists through the Harvard Innovation Laboratory, the company’s algorithm was trained on clinical data from 18,000 medical papers to mirror the literature referenced by physicians. Examples of data include 5 million patients and approximately 1,700 conditions.

You can check your symptoms online or browse the vast database of Buoy Health to figure out what might be wrong with your health. The chatbot thoroughly asks you about the details of your medical state and offers you various solutions and actionable steps to take.

Smart stethoscope. Getting to the ‘heart’ of the matter


An easy-to-use ‘smart’ stethoscope could help doctors detect heart failure earlier. Research compared the accuracy of the new technology, which uses AI, with the standard echocardiogram, which is usually carried out in hospitals or specialist clinics. More than 1,000 people from across London took part. The smart stethoscope identified people with heart failure 9 out of ten times

Hear it from a doctor.

” There’s currently no cure for heart failure, and so quick detection and treatment is key. This AI tool could fast-track people to get an earlier diagnosis, giving them access to life saving treatments and support much sooner." Nick Mills, British Heart Foundation, Professor of Cardiology at the University of Edinburgh

AI powered imaging. Eliminating errors in 3D medical scans.


3D medical scans, no doubt, are revolutionary techniques to produce a detailed CT scan, or an MRI. But comparing several 3D scans to understand what has changed since the last scan is time consuming and sometimes erroneous. However, with AI algorithms, it is possible to eliminate such hassles and discover the changes almost in real-time.

Medical imaging and diagnosis powered by AI should witness more than 40% growth to surpass USD 2.5 billion by 2024. – Global Market Insights

By leveraging AI in medical imaging, cancer tumor diagnosis can be improved by detecting it at a very early stage. Deep learning techniques like pattern recognition are enhancing the diagnosis approach and becoming a game changer in the imaging industry. This implementation of AI will help radiologists to improve productivity and accuracy. It will play a critical role in treating patients more efficiently and effectively. AI medical imaging addresses challenges concerning durability and image quality that have been difficult to solve before. It is transforming the healthcare industry in terms of increased diagnostic accuracy, personalized treatment planning, and improved clinical outcomes

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Acknowledgement: This article has been sourced from some of the most respected names in journalism across the world.

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