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- W4385760400 abstract "The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of human disease. CHARM, an AI algorithm described in this issue, 1 Nasrallah M.P. Zhao J. Tsai C.C. Meredith D. Marostica E. Ligon K.L. Golden J.A. Yu K.-H. Machine learning for cryosection pathology predicts the 2021 WHO classification of glioma. Med. 2023; 4: 526-540https://doi.org/10.1016/j.medj.2023.06.002 Abstract Full Text Full Text PDF Scopus (1) Google Scholar has the potential to streamline molecular classification, intraoperative diagnosis, surgical decision making, and trial enrollment for glioma patients. The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of human disease. CHARM, an AI algorithm described in this issue, 1 Nasrallah M.P. Zhao J. Tsai C.C. Meredith D. Marostica E. Ligon K.L. Golden J.A. Yu K.-H. Machine learning for cryosection pathology predicts the 2021 WHO classification of glioma. Med. 2023; 4: 526-540https://doi.org/10.1016/j.medj.2023.06.002 Abstract Full Text Full Text PDF Scopus (1) Google Scholar has the potential to streamline molecular classification, intraoperative diagnosis, surgical decision making, and trial enrollment for glioma patients. Machine learning for cryosection pathology predicts the 2021 WHO classification of gliomaNasrallah et al.MedJuly 7, 2023In BriefNasrallah et al. established the Cryosection Histopathology Assessment and Review Machine (CHARM), a context-aware machine-learning method for glioma diagnosis during surgery. They showed that CHARM identifies pathology imaging patterns indicative of molecular diagnoses of glioma defined by the new WHO classification. Full-Text PDF" @default.
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- W4385760400 title "Unlocking glioma genetics with deep learning" @default.
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- W4385760400 doi "https://doi.org/10.1016/j.medj.2023.07.008" @default.
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