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fishneck · Apr 25, 2024 · f8b4d51 · f8b4d51
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-											<h1>COnfidence-Based chaRacterization of Anomalies (<strong>COBRA</strong>)</h1>
-											<p>Joint work by Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi Schambra and Carlos Fernandez-Granda</p>
+											<h1> COBRA <br /> </h1>
+											<p> Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi Schambra and Carlos Fernandez-Granda</p>
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-										<p>Automatic assessment of impairment and disease severity is a key challenge in data-driven medicine. We propose a novel framework, COnfidence-Based chaRacterization of Anomalies (COBRA), to address this challenge, which leverages AI models trained exclusively on healthy subjects. The models are designed to predict a clinically-meaningful attribute of the healthy patients. When presented with data where the attribute is affected by the medical condition of interest, the models experience a decrease in confidence that can be used to quantify deviation from the healthy population. COBRA was applied to quantification of upper-body motion impairment in stroke patients, and severity of knee osteoarthritis from magneticresonance imaging scans.</p>
+										<p>Automatic assessment of impairment and disease severity is a key challenge in data-driven medicine. We propose a novel framework, <strong>COnfidence-Based chaRacterization of Anomalies (COBRA)</strong>, to address this challenge, which leverages AI models trained exclusively on healthy subjects. The models are designed to predict a clinically-meaningful attribute of the healthy patients. When presented with data where the attribute is affected by the medical condition of interest, the models experience a decrease in confidence that can be used to quantify deviation from the healthy population. COBRA was applied to quantification of upper-body motion impairment in stroke patients, and severity of knee osteoarthritis from magneticresonance imaging scans.</p>
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