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Artificial Intelligence In Healthcare: 10 Medical Fields A.I. Will Change Completely

September 1, 2021 at 11:00:00 PM

Artificial intelligence in healthcare has an unimaginable 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 for the better. Let’s take a look at the promising solutions it offers.


The Medical Futurist

Artificial Intelligence In Healthcare: 10 Medical Fields A.I. Will Change Completely


Dr. Bertalan Meskó

I am certain that healthcare will be the lead industrial area of such a revolution and one of the major catalysts for change is going to be artificial intelligence. Check the updated version of A Guide To Artificial Intelligence In Healthcare to understanding, anticipating and controlling artificial intelligence.


With the evolution of digital capacity, more and more data is produced and stored in the digital space. The amount of available digital data is growing at a mind-blowing speed, doubling every two years. In 2013, it encompassed 4.4 zettabytes, however by 2020 the digital universe – the data we create and copy annually – will reach 44 zettabytes, or 44 trillion gigabytes (!).

Usually, we make sense of the world around us with the help of rules and processes which build up a system. The world of Big Data is so huge that we will need artificial intelligence (A.I.) to be able to keep track of it.

A.I. 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 or Amazon’s Echo voice assistant services use natural language processing and do a set of valuable things, from driving directions to finding an open slot for a meeting. Imagine this efficiency in healthcare!

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

There are already several great examples of A.I. 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 – and not only to the richest medical institutions (because they are too expensive) or to a handful of experts (because they are too difficult to use).


Starting from the design of treatment plans through assistance in repetitive jobs to medication management or drug creation, artificial intelligence is already actively present in several areas of medicine. And it is only the beginning.

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

Integrating an A.I. assistant into the healthcare system could guide patients and optimise 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 optimised while they have a better healthcare experience.


The most obvious application of artificial intelligence in healthcare is data management. A.I. collecting, storing, normalising, tracing data is the first step in revolutionising the 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.

Google originally launched its Google Deepmind Health project, to mine the data of medical records in order to provide better and faster health services. Know more about Google’s plans in healthcare from our article, Google’s Masterplan for Healthcare.


A.I. algorithms can further assist in decision-making to improve the accuracy of diagnoses. For instance, several studies show that with the help of A.I., radiologists enhance the accuracy of cancer detection from radiological scans. In future scenarios, medical A.I. 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 analyse 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. Know more about IBM’s Moonshot Ambition In Healthcare in our article.


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 labour 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 A.I.-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 forthcoming future.


Everybody, please welcome the world’s first virtual nurse, Molly developed by the medical start-up It has a smiling, amiable face coupled with a pleasant voice and its exclusive goal is to help people with monitoring their condition and treatment. The interface uses machine learning to support patients with chronic conditions in-between doctor’s visits. It provides proven, customized monitoring and follow-up care, with a strong focus on chronic diseases.

Also, there is already a solution for monitoring whether patients are taking their medications for real. The AiCure app supported by The National Institutes of Health uses a smartphone’s webcam and A.I. to autonomously confirm that patients are adhering to their prescriptions, or with better terms, supporting them to make sure they know how to manage their condition. This is very useful for people with serious medical conditions, for patients who tend to go against the doctor’s advice and participants in clinical trials.


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 invent 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. A.I. 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 affect today’s healthcare and how innovations reach everyday medicine. A.I. slashes time and cost of drug discovery and development significantly.

A.I. pharma startup Insilico Medicine in 2019 identified a potential new drug in only 46 days. Its software achieved this by analysing hordes of data that would take humans years to go through. During the Ebola epidemic in 2015, Atomwise used its A.I. 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 A.I. 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 A.I. 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 analysed 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, Zorgprisma Publiek analyzes the invoices and uses IBM Watson in the cloud to mine the data. They can tell if a doctor, clinic or hospital makes mistakes repetitively in treating a certain type of condition in order to help them improve and avoid unnecessary hospitalizations of patients.


First and foremost, we have to tear down the prejudices and fears regarding artificial intelligence and help the general population understand how A.I. could be beneficial and how we can fight its possible dangers. The biggest fear is that A.I. will become so sophisticated that it will work better than the human brain and after a while, it will aim to take control over our lives. Stephen Hawking even said that the development of full artificial intelligence could spell the end of the human race. Elon Musk agreed (although he says he’s currently building humanoid robots).

I do not think there’s a Terminator apocalypse coming. But I agree with those who stress the need to prepare for the use of artificial intelligence in healthcare appropriately. We need these steps to avoid the pitfalls of the utilization of A.I.:

1. creation of ethical standards which are applicable to and obligatory for the whole healthcare sector.

2. the gradual development of A.I. in order to give some time for mapping of the possible downsides.

3. for medical professionals: get basic knowledge about how A.I. works in a medical setting to understand how such solutions might help them in their everyday job.

4. for patients: getting accustomed to artificial intelligence and discovering its benefits for themselves – e.g. with the help of Cognitoys which support the cognitive development of small children with the help of A.I. in a fun and gentle way or with such services as Siri.

5. for companies developing A.I. solutions (such as IBM): even more communication towards the general public about the potential advantages and risks of using A.I. in medicine.

6. for decision-makers at healthcare institutions: doing all the necessary steps to be able to measure the success and the effectiveness of the system. It is also important to push companies towards offering affordable A.I.-solutions since it is the only way to bring the promise of science fiction into reality and turn A.I. into the stethoscope of the 21st century.

If we succeed, huge medical discoveries and treatment breakthroughs will dominate the news not from time to time, but several times a day. If you ever come across or use a narrow A.I. system, you will understand my optimism.

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