New York, New York, United States - 10-05-2022 (PR Distribution™) - 
Nowadays, artificial intelligence is being widely introduced into various areas, with its scope of application in medicine expanding year after year. In present-day clinics, AI is no longer an innovation; it is a standard technology that transforms the way medical organizations work.
1. Triage
One of the primary tasks that must be quickly resolved when patients are seeking medical help is to accurately assess who needs help right now and who can wait for a while. This sorting procedure, known as triage, is actively supported by AI technologies.
One such digital triage system, developed by Babylon Health, helps to analyze patients' call center requests. As a result, some patients are recommended to get immediate assistance, while others are advised to learn more about their disease and its symptoms (i.e., their cases are considered non-emergent). The system has been adopted by the UK's National Health Service and already saves costs on call center wages.
2. Switching to electronic documents
Systems capable of analyzing large amounts of data are also actively integrated into the healthcare systems of several countries. One of the states demonstrating the greatest progress in this area is South Korea: it initiated the digitalization of medical documents as far back as 2003. Seoul Bundang Hospital became the first “paperless” medical facility; by 2022, similar systems have been adopted by over 90% of national hospitals.
One of Bundang’s most impactful developments is its BESTCare 2.0 system: during the first wave of coronavirus in March 2020, it promptly traced all contacts of infected persons, thus making it possible to avoid a total lockdown.
3. Diagnostics
One of the most significant diagnostic solutions was designed by Zebra ?edical, an Israel-based AI startup, and is used by medics in several countries to analyze CT scans and spot lung, liver, or breast cancer. To optimize operational costs and the workflow, Zebra offered hospitals to move all the algorithms to the cloud instead of paying for hosting their servers. In that case, only $1 will be charged for making and analyzing a scan.
4. Personalized treatment
Artificial intelligence boosts the efficiency and accuracy of medical prescriptions, as well as optimizes surgical treatment. For instance, Accuray’s CyberKnife improves the precision of surgeries: this AI-based system analyzes the patient’s body specifics and the tumor location to make surgical interventions less traumatic.
Another helpful tool, designed by Vicarious Surgical, combines the advantages of virtual reality, artificial intelligence, and robotic surgery and enables it to perform the least invasive surgeries.
5. Hospital work optimization
Any medical facility is a complex mechanism, with doctors, nurses, and many other personnel members contributing to its operations. Its stable functioning is the prerequisite for fast and precise medical assistance.
AKASA is one of the most popular AI- and ML-based systems used in the US, already integrated into hundreds of hospitals all over the nation. It can be configured to meet the requirements of a specific medical facility. For example, the system helps to automate claim management, reducing the time needed to process a claim from seven minutes to one and increasing the number of processed claims. The medical personnel do not need to waste their time on paperwork and can focus instead on the patients and their problems.
6. Clinical trials
Another scope of AI application is clinical trials, with machines already performing tasks like finding new drugs, reprofiling existing ones, and finding patients that match the trial criteria.
For instance, scientists at Mount Sinai Medical Center performed an AI-assisted topological data analysis that studied medical records and genotype information of patients with type 2 diabetes, divided them into three subtypes, and forecasted the response of each subtype to the drug during the trials.
Rustam Gilfanov is a private investor, philanthropist and a venture partner of the LongeVC fund.
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