IBM forms Watson Health medical imaging collaborative to improve doctors' work

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IBM this week announced it has created a Watson Health medical imaging collaborative, a global initiative including more than fifteen leading health care entities such as academic medical centers, ambulatory radiology providers and imaging technology companies. The collaborative aims to bring cognitive imaging into daily practice to help doctors address cancers, diabetes, eye, brain and heart diseases. Members of the collaborative intend to put Watson to work to extract insights from previously'invisible' unstructured imaging data and combine that with a variety of data from other sources. In doing so, the efforts may help doctors make personalised care decisions relevant to a specific patient while building a body of knowledge to benefit the broader patient populations. This information may include data from electronic health records, radiology and pathology reports, lab results, doctors' progress notes, medical journals, clinical care guidelines and published studies.


IBM forms Watson Health medical imaging collaborative ZDNet

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After several months of beefing up the Watson Health Unit, IBM on Wednesday announced it has recruited 16 other entities involved in the health care sector to from a new Watson Health medical imaging collaborative. The global collaborative aims to advance cognitive imaging in a range of medical specialties, from eye care to the treatment of heart and brain disease. The group plans to use Watson to analyze previously "invisible" unstructured imaging data, found in places such as radiology and pathology reports, as well as broad swaths of data collected from sources like population-based disease registries. "There is strong potential for systems like Watson to help to make radiologists more productive, diagnoses more accurate, decisions more sound, and costs more manageable," Nadim Michel Daher, a medical imaging and informatics analyst for Frost & Sullivan, said in a statement. "This is the type of collaborative initiative needed to produce the real-world evidence and examples to advance the field of medical imaging and address patient care needs across large and growing disease states."


IBM forms Watson Health medical imaging collaborative ZDNet

#artificialintelligence

After several months of beefing up the Watson Health Unit, IBM on Wednesday announced it has recruited 16 other entities involved in the health care sector to from a new Watson Health medical imaging collaborative. The global collaborative aims to advance cognitive imaging in a range of medical specialties, from eye care to the treatment of heart and brain disease. The group plans to use Watson to analyze previously "invisible" unstructured imaging data, found in places such as radiology and pathology reports, as well as broad swaths of data collected from sources like population-based disease registries. "There is strong potential for systems like Watson to help to make radiologists more productive, diagnoses more accurate, decisions more sound, and costs more manageable," Nadim Michel Daher, a medical imaging and informatics analyst for Frost & Sullivan, said in a statement. "This is the type of collaborative initiative needed to produce the real-world evidence and examples to advance the field of medical imaging and address patient care needs across large and growing disease states."


IBM Researchers Bring AI to Radiology at RSNA 2016 - IBM Blog Research

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"When my father was misdiagnosed and administered the wrong medication placing him in a coma nearly 20 years ago, I saw firsthand the need for technology to help physicians make accurate decisions," said Tanveer Syeda-Mahmood, IBM Fellow and Chief Scientist of the Medical Sieve Radiology Grand Challenge Project at IBM Research – Almaden in San Jose, Calif. This week in Chicago, Dr. Syeda-Mahmood's mission meets the real world as IBM Research debuts a new Watson-powered demo that shows the future of Artificial Intelligence (AI) in radiology. The demo is the result of a shared vision by Dr. Syeda-Mahmood and Dr. Eugene Walach from IBM Research – Haifa to help radiologists make accurate patient diagnoses quickly and easily. In any given day, radiologists can review up to thousands of medical images to make health diagnoses. To date, accuracy has relied mainly on medical professionals piecing together multiple sources of clinical information visually and manually to make critical decisions, including electronic health records, research publications and other data.


Artificial intelligence, machine learning find role in radiology

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Artificial intelligence and machine learning capabilities are beginning to make an impact within radiology, as vendors start rolling out initiatives to assist professionals in making diagnoses. The radiology profession is ripe for technology--as radiologists deal with an increasing number of images and bear more responsibility in the clinical process. For example, radiologists now are being called upon to determine what course of treatment might be less invasive, thus reducing cost, patient recovery times and the risk of complications. Or they typically are asked to assess the rate of progression of a disease such as cancer, to determine what course of treatment is most appropriate. The use of advanced technology could be considered disruptive and perhaps threatening to some radiologists, but it will become essential for professionals to do their jobs effectively, says Leo Wolansky, neuroradiologist and professor of Radiology at University Hospitals, Cleveland.