High Tech Advancing Future of Personalized Cancer Care

IBM Watson and Personalized Cancer CareMemorial Sloan-Kettering Cancer Center, IBM to Collaborate
in Applying Watson Technology to Help Oncologists

IBM Watson combined with MSKCC’s clinical knowledge will help
physicians access and integrate latest science and knowledge

New York City – 22 Mar 2012: Memorial Sloan-Kettering Cancer Center and IBM have agreed to collaborate on the development of a powerful tool built upon IBM Watson in order to provide medical professionals with improved access to current and comprehensive cancer data and practices. The resulting decision support tool will help doctors everywhere create individualized cancer diagnostic and treatment recommendations for their patients based on current evidence.

The initiative will combine the computational power of IBM Watson and its natural language processing ability with MSKCC’s clinical knowledge, existing molecular and genomic data and vast repository of cancer case histories, in order to create an outcome and evidence-based decision support system. The goal is to give oncologists located anywhere the ability to obtain detailed diagnostic and treatment options based on updated research that will help them decide how best to care for an individual patient.

The IBM Watson system gained fame by beating human contestants on the television quiz show Jeopardy! It can interpret queries in natural language and uses statistical analysis, advanced analytics and a powerful array of processors to search millions of pages in seconds and deliver evidence-based statistically-ranked responses.

For more Information:

Click on the infographic of the Future of Personalized Cancer Care for a larger version

How IBM Watson is Transforming Healthcare

There are over 12,000 diseases in the world. Some take years to diagnose and treat. This, combined with medical knowledge that doubles every 5 years often makes it difficult for doctors to keep up. IBM is working on new solutions based on its Watson supercomputer  to help doctors with faster and more accurate diagnoses.

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