Evaluating AI systems under uncertain ground truth: a case study in dermatology

For safety, AI systems in health undergo thorough evaluations before deployment, validating their predictions against a ground truth that is assumed certain. However, this is actually not the case and the ground truth may be uncertain. Unfortunately, this is largely ignored in standard evaluation of...

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Hauptverfasser:	Stutz, David, Cemgil, Ali Taylan, Roy, Abhijit Guha, Matejovicova, Tatiana, Barsbey, Melih, Strachan, Patricia, Schaekermann, Mike, Freyberg, Jan, Rikhye, Rajeev, Freeman, Beverly, Matos, Javier Perez, Telang, Umesh, Webster, Dale R, Liu, Yuan, Corrado, Greg S, Matias, Yossi, Kohli, Pushmeet, Liu, Yun, Doucet, Arnaud, Karthikesalingam, Alan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Learning Statistics - Machine Learning Statistics - Methodology
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