Artificial Intelligence Will Redesign Healthcare



In June 2021, I gave a keynote speech at the CMSA 2021 Virtual Conference, concentrating on how automation, most notably artificial intelligence, will affect care in medicine. This article was explicitly rewritten as a follow-up to that speech.

Artificial intelligence in healthcare has incredible potential. Within the next couple of years, it will revolutionize every area of our life, including medicine. I am fully convinced that it will redesign healthcare completely, and it will be for the better. Let me show you how.

AI is already on our wrists, in our cars, in the searches we do or what we are offered to buy. Siri, Alexa, Cortana, OK Google and Amazon’s Echo voice assistant services use natural language processing and do a set of valuable things, from providing driving directions to finding an open slot for a meeting. Imagine this efficiency in healthcare!

There are already several excellent examples of AI in healthcare showing potential implications and possible future uses that could make us quite optimistic. However, these solutions will only revolutionize medicine and healthcare if they are available to the average, mainstream users—not only to the wealthiest medical institutions (because they are too expensive) or to a handful of experts (because they are too difficult to use).


Artificial intelligence in healthcare and medicine could better organize patient routes or treatment plans and provide physicians with literally all the information they need to make a good decision.

Integrating an AI assistant into the healthcare system could guide patients and optimize the time spent during their medical journey with a Waze-like approach. It can determine where the queue is shorter and which test will take less time to perform for each patient. By connecting with non-emergency medical transportation (NEMT) rides offered by ride-hailing platforms like Uber and Lyft, the algorithm can suggest which healthcare facility will be more time-efficient to visit and direct patients. In this way, the time spent by each patient is optimized while they have a better healthcare experience.


The most obvious application of artificial intelligence in healthcare is data management. AI collecting, storing, normalizing and tracing data is the first step in revolutionizing existing healthcare systems. These bureaucratic tasks and managing health IT and EHR systems are, in fact, among the significant reported causes of physician burnout. But these tasks aren’t related to the practice of medicine. Algorithms can automate such administrative tasks to free up valuable time for healthcare professionals to dedicate to their patients and elucidate medical conditions.


Moreover, AI algorithms can further assist in decision-making to improve the accuracy of diagnoses. For instance, several studies show that with the help of AI, radiologists enhance the accuracy of cancer detection from radiological scans. In future scenarios, medical AI trained via reinforcement learning could discover treatments and cures for conditions when human medical professionals could not.

IBM Watson launched its dedicated program for oncologists, providing clinicians with evidence-based treatment options. Watson for Oncology has an advanced ability to analyze the meaning and context of structured and unstructured data in clinical notes and reports that may be critical to selecting a treatment pathway. By combining attributes from the patient’s file with clinical expertise, external research, and data, the program identifies potential treatment plans for a patient.


Physicians, nurses and other medical staff members have plenty of cumbersome, monotonous and repetitive tasks to complete every day. According to a study, in the United States the average doctor spends 8.7 hours per week on administration ( But these types of functions and procedures can be automated—and they indeed should be. Artificial intelligence-based solutions will eliminate the need for human labor and will replace human resources in medical jobs that people didn’t like anyway. Such solutions will ease medical professionals’ burdens, for example, in administration or after-hours charting.


Based in the UK, Babylon Health built a patient-centered remote consultation service. It already works in Rwanda and also in the UK, offering medical AI-consultation based on personal medical history and common medical knowledge. Users report the symptoms of their illness to the app, which checks them against a database of diseases using speech recognition. After taking into account the patient’s history and circumstances, Babylon offers an appropriate course of action. Remote consultation gained momentum with the pandemic, and it will remain with us in the future.


Artificial intelligence will have a significant impact on genetics and genomics as well. Deep Genomics aims at identifying patterns in giant data sets of genetic information and medical records, looking for mutations and linkages to disease. They are inventing a new generation of computational technologies that can tell doctors what will happen within a cell when DNA is altered by genetic variation, whether natural or therapeutic. AI has the biggest potential to analyze vast amounts of data and offer insights to create personalized solutions and targeted treatments.


Developing pharmaceuticals through clinical trials sometimes takes more than a decade and costs billions of dollars. Speeding this up and making it more cost-effective would have an effect on today’s healthcare and how innovations reach everyday medicine. AI slashes time and cost of drug discovery and development significantly.

AI pharma startup Insilico Medicine in 2019 identified a potential new drug in only 46 days. Its software achieved this by analyzing hordes of data that would take humans years to go through. During the Ebola epidemic in 2015, Atomwise used its AI algorithm to identify two drugs with significant potential to reduce Ebola infectivity. It accomplished this effort in less than a day.

Another excellent example of using big data for patient management is Berg Health, a Boston-based biopharma company that mines data to determine why some people survive diseases and thus improve current treatment or create new therapies. They combine AI with the patients’ biological data to map out the differences between healthy and disease-friendly environments and help discover and develop drugs, diagnostics and healthcare applications.


An open AI ecosystem refers to the idea that with an unprecedented amount of data available, combined with advances in natural language processing and social awareness algorithms, applications of AI will become increasingly more useful to consumers.

It is especially true in medicine and healthcare. There is so much data to use: patient medical history records, treatment data—and information coming from wearable health trackers and sensors. This vast amount of data could be analyzed in detail to provide patients who want to be proactive with better suggestions about lifestyle. It could also serve healthcare with instructive pieces of information about how to design healthcare based on the needs and habits of patients.


97% of healthcare invoices in the Netherlands are digital, containing data regarding the treatment, the doctor and the hospital. These invoices could be easily retrieved. A local company, Vektis, analyzes the invoices and uses AI in the cloud to mine the data. They can tell if a doctor, clinic or hospital makes mistakes repetitively in treating a specific type of condition to help them improve and avoid unnecessary hospitalizations of patients.


First and foremost, we need to tear down the prejudices and fears regarding artificial intelligence and help the general population understand how AI could be beneficial and how we can fight its possible dangers and use AI in healthcare appropriately. We need ethical standards which are applicable to and obligatory for the entire healthcare sector and give some time for mapping of the possible downsides with gradual development of AI systems.

Medical professionals need to acquire basic knowledge about how AI works in a medical setting. Patients should get accustomed to artificial intelligence and discover its benefits for themselves, and companies developing AI solutions should put even more emphasis in communicating about the potential advantages and risks of using AI in medicine.

At the same time, decision-makers at healthcare institutions should do all the necessary steps to measure the system’s success and effectiveness. It is also essential to push companies toward offering affordable AI solutions since it is the only way to bring the promise of science fiction into reality and turn AI into the stethoscope of the 21st century. Rather than a competition, the technology should be seen as cooperation that amplifies human performance.

However, there are responsibilities and duties which technologies cannot perform. While algorithms can sift through millions of pages of documents in seconds, AI will never be able to do the Heimlich maneuver. There will always be tasks where humans will be faster and more reliable than technology.

Healthcare professionals with good social skills, empathy and compassion have an exciting future ahead, thriving in an AI world.

dr bertalan mesko

Dr. Bertalan Meskó, MD, PhDis The Medical Futurist and the director of The Medical Futurist Institute analyzing how science fiction technologies can become a reality in medicine and healthcare. As a geek physician with a PhD in genomics, he is also an Amazon Top 100 author. He is also a private professor at Semmelweis Medical School, Budapest, Hungary. The Medical Futurist:


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