Dr. James McCaffrey of Microsoft Research: When multi-class data is skewed toward one or more classes, it's very important to analyze accuracy by class. A multi-class classification problem is one ...
Producing the highest accuracy, the 9-gene set produced became the basis of the final classifier. When applied to multiple STS datasets, the model consistently separated patients into low-risk and ...
Please provide your email address to receive an email when new articles are posted on . Use of the Envisia Genomic Classifier impacted physician decision-making for evaluation of interstitial lung ...
A predictive model utilizing serum metabolic profiles was able to distinguish ovarian cancer from control samples with 93% accuracy, according to a new study. Machine learning–based classification ...
Pediatric sarcomas provide a unique diagnostic challenge. There is considerable morphologic overlap between entities, increasing the importance of molecular studies in the diagnosis, treatment, and ...
Multi-Class Classification Using New PyTorch Best Practices, Part 2: Training, Accuracy, Predictions
Following new best practices, Dr. James McCaffrey of Microsoft Research revisits multi-class classification for when the variable to predict has three or more possible values. This is the second of ...
Adaptive AI-driven clinical decision-making in oncology through digital twins and large-scale imaging biomarkers. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract ...
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