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Found 4 papers, 4 papers with code
Predicting Ovarian Cancer Treatment Response in Histopathology using Hierarchical Vision Transformers and Multiple Instance Learning
For some therapies, it is not possible to predict patients' responses, potentially exposing them to the adverse effects of treatment without any therapeutic benefit.
Artificial Intelligence in Ovarian Cancer Histopathology: A Systematic Review
The inclusion criteria required that research evaluated AI on histopathology images for diagnostic or prognostic inferences in ovarian cancer.
Efficient subtyping of ovarian cancer histopathology whole slide images using active sampling in multiple instance learning
Weakly-supervised classification of histopathology slides is a computationally intensive task, with a typical whole slide image (WSI) containing billions of pixels to process.
The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-rays
Model performance results have been exceptional when training and testing on open-source data, surpassing the reported capabilities of AI in pneumonia-detection prior to the COVID-19 outbreak.
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