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In this week’s episode, we’ll be looking at a paper recently published in “ACR Open Rheumatology” titled: “Machine Learning Applied to Patient-Reported Outcomes to Classify Physician-Derived Measures of Rheumatoid Arthritis Disease Activity“. This study used machine learning tools to investigate whether longitudinal patient-reported outcome data can be a proxy for Clinical Disease Activity Index (CDAI), presenting interesting findings that may impact the practice of rheumatology.
Our guest this week is the paper’s first author, Dr. Jeffrey Curtis. Dr. Curtis is the Marguerite Jones Harbert – Gene V. Ball Endowed Professor in Rheumatology and Immunology at the University of Alabama at Birmingham. He has many accolades to his name, including being a prior winner of the Henry Kunkel Young Investigator Award and being a member of the American Society for Clinical Investigation.
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In this week’s episode, we’ll be looking at a paper recently published in “ACR Open Rheumatology” titled: “Machine Learning Applied to Patient-Reported Outcomes to Classify Physician-Derived Measures of Rheumatoid Arthritis Disease Activity“. This study used machine learning tools to investigate whether longitudinal patient-reported outcome data can be a proxy for Clinical Disease Activity Index (CDAI), presenting interesting findings that may impact the practice of rheumatology.
Our guest this week is the paper’s first author, Dr. Jeffrey Curtis. Dr. Curtis is the Marguerite Jones Harbert – Gene V. Ball Endowed Professor in Rheumatology and Immunology at the University of Alabama at Birmingham. He has many accolades to his name, including being a prior winner of the Henry Kunkel Young Investigator Award and being a member of the American Society for Clinical Investigation.
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