Topic · Artificial Intelligence · Computer Science
OpenAlex topic; a paper is listed when OpenAlex scores it at least 0.5 for this topic.
275 papers
Michael Nalisnik, Mohamed T. Amgad, Sanghoon Lee…·Lee Cooper
HistomicsML enables interactive machine learning for analyzing histology images to identify phenotypes and predict survival in gliomas.
Jacob S. Sarnecki, Laura DeLong Wood, Christopher Lee Wolfgang…·Pei-Hsun Wu
The paper identifies tissue morphology biomarkers in long-term PDAC survivors using digital pathology and machine learning, finding reduced heterogeneity and extra-tumoral space features correlate with better survival.
Wentao Zhu, Chaochun Liu, Wei Fan, Xiaohui S. Xie
On LIDC-IDRI, gradient boosting on 3D dual path network features reaches 90.44% accuracy on annotated nodules; with a 3D Faster R-CNN detector, patient-level accuracy is 81.41%, 99% of doctors' average.
Wentao Zhu, Qi Lou, Yeeleng S. Vang, Xiaohui S. Xie
This paper proposes deep multi-instance networks for whole mammogram classification without requiring manual annotations, showing robustness on the INbreast dataset.
An end-to-end fully convolutional network with a positional prior, conditional random field structural learning, and adversarial training segments mammographic masses on INbreast and DDSM-BCRP.