IBM’s Biomedical Analytics Platform Helps Doctors Personalize Treatment

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Haifa, Israel: IBM recently announced it has developed a unique biomedical analytics platform for personalized medicine that could enable doctors to better advise on the best course of medical treatment. This could lead to smarter and more personalized healthcare in a wide-range of areas, including cancer management, hypertension, and AIDS care.

Scientists from IBM Research are collaborating with the Fondazione IRCCS Istituto Nazionale dei Tumori, a major research and treatment cancer center in Italy, on the new decision support solution. This new analytics platform is being tested by the Institute’s physicians to personalize treatment based on automated interpretation of pathology guidelines and intelligence from a number of past clinical cases, documented in the hospital information system.

Selecting the most effective treatment can depend on a number of characteristics including age, weight, family history, current state of the disease and general health.  As a result, more informed and personalized decisions are needed to provide accurate and safe care.

IBM’s latest healthcare analytics solution, Clinical Genomics (Cli-G), can integrate and analyze all available clinical knowledge and guidelines, and correlate it with available patient data to create evidence that supports a specific course of treatment for each patient. Developed at IBM Research – Haifa, the new prototype works by investigating the patient’s personal makeup and disease profile, and combines this with insight from the analysis of past cases and clinical guidelines. The solution may provide physicians and administrators with a better picture of the patient-care process and reduce costs by helping clinicians choose more effective treatment options.

In addition to supporting decision-making about treatment, it can provide administrators at Fondazione IRCCS Istituto Nazionale dei Tumori with an aggregated view of patient care, enabling them to evaluate performances and using this knowledge to streamline processes for maximum safety. For example, hospital administrators can drill down into the data to better understand what the guidelines were for insights, what succeeded, and whether treatment quality has improved.

Any patient data securely collected from hospitals and health organizations is ‘de-identified’ or made anonymous through the removal of personal identifying details. The IBM system does not need to know which individuals the information came from in order to draw conclusions. It works by identifying similar cases based on age, sex, symptoms, diagnosis, or other related factors.

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