Tag: computational pathology

A customised convolutional neural network detected mitotic figures in breast cancer histopathology images with a reported accuracy of 96.6 percent, ...

A systematic review of 51 studies finds that machine learning assessment of tumor-infiltrating lymphocytes in breast cancer histopathology is technically ...

A computational polarimetric imaging framework combining differential Mueller matrix decomposition, wide-field image stitching and pseudo-color visualization revealed depolarization as a ...

A narrative review maps how machine learning and deep learning now span oral cancer care from smartphone lesion triage and ...

Pancreatic ductal adenocarcinoma remains one of medicine's most unforgiving diagnoses. Despite decades of progress in surgical technique and chemotherapy, the ...

A multimodal transformer-based AI framework achieved an AUC of 0.727 on preoperative endoscopic biopsy slides for predicting lymph node metastasis ...

A retrospective study in high-grade serous tubo-ovarian carcinoma found that HRDPath inferred homologous recombination deficiency from pathology slides with an ...

A retrospective study of 165 surgically treated patients found that machine-learning analysis of whole-slide images linked CD8-positive immune-cell density, Foxp3-positive ...

A new deep learning architecture called TexTNet integrates local binary pattern texture features into a Swin Transformer's attention mechanism to ...

A new interpretable AI model called PRISM combines pathology slides with transcriptomic pathway data to sharpen progression-risk prediction in early-stage ...