AI as a medical service: what Healthcare functions can be made with Machine Learning?

The majority of medical care providers question whether to use AI technologies within Healthcare industry. Lack of information about how it works and what benefits it can bring is the most frequent cause of it. There are several areas where AI can make healthcare processes better:


Proсessing capabilities of AI perfectly suit for analyzing medical images such as x-rays. Using patterns based on clinical case studies, AI can evaluate patients’ health status and detect severe illnesses like cancer on the early stage. Diagnostics has been also improved thanks to rising of Internet of Medical Things (IoMT) and the way it works in a combination with AI. Currently IoMT is used mostly to gather data from various devices, optimize workflow and integrate medical devices. Reports based on the collected data help to determine diagnoses and choose treatment approaches more effectively.


AI-driven software brings simplified everyday care delivery into your mobile devices: smartphone, smart watches, fitness bracelets and so on. Personal AI health assistants can improve selection of individual treatment, recovery plans, meditation programs and care recommendations for you. Usually, such software tracks heart rate, activity level, sleep and other physiological processes. Continuous analysis of such data helps AI-driven applications to identify critical issues preventing users from accidents like heart attack.

Service operations

Implementation of AI can cut costs of administration services in medical and care centers. AI bots can serve the majority of administration duties including scheduling, management, document flow, interaction with patients both online and offline. It can gather data from your mobile devices and instantly deliver it to the attending doctor. Then the data is processed using deep learning algorithms.

Caregiving and surgery assistants

Hospitals have already started to apply AI technologies in caregiving and test the capabilities of virtual nurses. Alexa-like bots serve as a nurse reminding their patients about taking medicine, answering patients’ questions, collecting and transferring important data to doctors. Robot-assisted surgery is a new innovative approach that is considered to be the most perspective in Healthcare industry. During surgeries digital AI-driven tools can also give recommendations combining previous surgeries data with information about the ongoing process. This way health facilities can optimize medical equipment costs.

Clinical trials and drug discovery

Integrated AI solutions can help to collect and analyze important data and track the progress within clinical trials. Automation provides research centers with digital records that are more effective than the paper ones. AI saves time for drug discovery processing the information about testings faster. This approach gives an opportunity to conduct primary checks before testing of a new drug on humans. The testing and data analysis results simplify matching trial to the right patient. For example, applications like ResearchKit and CareKit considering specific users’ health conditions like autism and Parkinson’s disease are used in clinical studies all over the world.

As any innovation, AI-driven Healthcare approaches have their own risks including unethical decision making and mistakes of recommendation mechanism. That is why AI adoption should be started with primary tasks like management and going deeper into surgeries and drug discovery. The data used for deep learning should be chosen carefully as Artificial Intelligence relies on particular patterns excluding empathy and specific patient conditions.

Despite the technological progress and Machine Learning capabilities, AI in Healthcare industry still needs a human intervention – both in work and development. If you want to bring innovative quality to your services, Exposit engineers will provide you with suitable AI-driven Healthcare solution.