Healthcare and medicine are considered as promising areas for the adoption of artificial intelligence (AI). The use of AI can bring the accuracy of diagnosis to a qualitatively new level, make life easier for patients with various diseases, increase the speed of development and release of new drugs.

The largest and most discussed project for applying AI in medicine is IBM Watson cognitive system. Since 2015, IBM, a system developer company, has been forming partnerships with Apple to transfer health data from iPhone and Apple Watch owners (with their permission) to the IBM cloud. Subsequently, this health information may be shared with doctors and insurance companies for the preparation of personal health care offers.

Other IBM partner companies also benefit from the collaboration. For example, pharmaceutical company Johnson & Johnsonuses cognitive system data to create service that helps patients prepare for surgery and recover after it. Medtronic, working with IBM’s cloud platform, intends to improve its heart implants and develop customized solutions for diabetic patients.

IBM Watson has also been successfully applied in oncology, cardiology, diagnostics, as well as medical imaging (e.g. MRI images) and clinical trials of drugs.  IBM Watson training required analysis of 30 billion medical images, 50 million anonymous electronic medical records, as well as 605,000 medical symptoms.

IBM also developed a software — IBM Care Management, which provides the capabilities necessary for healthcare management. This software allows to identify clients in need of healthcare services, assess their needs, monitor compliance with the requirements of specialists, and monitor results. As a result, a comprehensive view of the individual client is formed and allows to provide him/her with health services.

Another project developed by a British company that is part of Google is called DeepMind Health. This artificial intelligence system can process hundreds of thousands of medical records in a few minutes and allocate the necessary information from them. In addition, using a million anonymous tomograph-derived eye images, DeepMind researchers together with staff at Moorfields Hospital (UK) work on the creation of algorithms based on machine learning technologies that would help to detect early signs of two eye diseases — wet age-related macular dystrophy and diabetic retinopathy.

The Israel company MedyMatch Technology, which has only 20 people, has developed an AI and Big Data solution, thanks to which doctors can more accurately diagnose stroke. To do this, in real time, the MedyMatch system compares a patient’s brain image to hundreds of thousands of other images that are in her “cloud” and identifies even a small deviation from the normal , which a specialist cannot always notice, thus reducing the probability of error in the diagnosis and treatment to a minimum.

Summing up the above, capabilities of AI and the prospects for its introduction in medicine are impressive and suggest that soon AI will become the most ordinary assistant for most health professionals.

References:

1. Gusev, Aleksander. (2017). Искусственный интеллект в медицине и здравоохранении.
2. Aggarwal, Mayank & Madhukar, Mani. (2017). IBM’s Watson Analytics for Health Care:. 10.4018/978-1-5225-1002-4.ch007.
3. Creation of Watson Health division: Medical data from Apple devices are flocking to IBM