Artificial Intelligence on Medical Data

Proceedings of International Symposium, ISCMM 2021

Medical information is generated ubiquitously in many settings ranging from personal physician offices and hospitals to government and non-government health agencies. Some of these data are individual data points of single patients, while others are conglomeration of health demographic data in large server databases. Then, there are data that are generated in clinical laboratories testing different healthy persons for screening for disease along with basic science research that are being translated to clinical trials. The analysis of such data may supply insights for decision making from the level of individual patient/health worker to large-scale policy making for the entire population of country, region or racial groups. Such diverse generation of data has given rise to many developments in the method to analyze data. One of the primary concerns of these platforms has been sieving and sifting proper analyzable data.

Many computer scientists and health professionals have been working in tandem, but there are also many individual efforts that go undocumented. Thus, this second symposium of ISCMM 2021 was conducted to encourage such individuals and small groups to present their findings and observations. Many of them have innovative ideas or findings that get drowned by a cacophony of larger groups pushing their agendas.

The symposium gave emphasis to use of artificial intelligence in medical images. This could be microscopic or radiologic images and image obtained by signal processing of individual patient to images generated when bid population data visualization is done.