Medial Research Ltd.

Nir Kalkstein

Yaron Kinar

Varda Shalev

Gabriel Chodick

Inbal Goldshtein

Arturo Weschler

A method of evaluating lung cancer risk by generating a set of features comprising a plurality of current blood test results from a blood collected from a target individual, providing at least one classifier generated according to an analysis of a plurality of respective historical blood test results of each of another of a plurality of sampled individuals, and evaluating, using a processor, a lung cancer risk of said target individual by classifying said set of features using said at least one classifier. Each of said plurality of historical and current blood test results comprises results of one or more selected blood tests such as white blood cells blood test results, biochemistry test results, platelets blood test results including at least one of platelets count and mean platelet volume (MPV) and/or a combination of smoking history and red cell test results.

Methods and systems of evaluating a risk of lung cancer

A method of evaluating gastrointestinal cancer risk. The method comprises generating a set of features comprising a plurality of current blood test results from a blood collected from a target individual, providing at least one classifier generated according to an analysis of a plurality of respective historical blood test results of each of another of a plurality of sampled individuals, and evaluating, using a processor, a gastrointestinal cancer risk of the target individual by classifying the set of features using the at least one classifier.

Methods and systems of evaluating a risk of a gastrointestinal cancer

There is provided a method of computing computed pathological indication(s), comprising: receiving an indication of values of current laboratory test results calculated based on an automated analysis of laboratory sample(s) collected from a target individual, selecting classifier(s) according to an analysis of the indication of values of the current laboratory test results, determining additional laboratory test(s) according to the analysis of the indication of values of the current laboratory test results and/or the selected classifier(s), generating instructions for automatic execution of second automatic laboratory testing device(s) on the laboratory sample(s) to obtain a second indication of a second value of the additional laboratory test(s), and evaluating computed pathological indication(s) by applying the selected classifier(s) to the indication of values of the current laboratory test results and the second indication of the second value of the additional laboratory test result(s).

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Herzlia, Israel

Nir Kalkstein