Ultrasound is widely used in breast cancer diagnosis. While it can effectively show that a lump is filled with fluid – indicating it is unlikely to be cancer – it cannot reliably determine whether a ...

Leveraging Digital Technology and Artificial Intelligence to Describe the Real-World Belgian Chronic Lymphocytic Leukemia Patient Population: The BE-CLLEAR Study We analyzed 21,364 pathology reports ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...

The term “brain tumor” carries a particularly scary connotation. And if you’re a fan of TV medical dramas, you may think they’re quite common. However, less than 1% of Americans are living with a ...

Annabell Downey’s breast cancer was diagnosed only after she collapsed and was taken to hospital — by which point it had already spread. Her experience highlights growing evidence that having a ...

1 Department of Mathematics & Statistical Sciences, Jackson State University, Jackson, MS, USA. 2 Department of Public Health, California State University, Fullerton ...

Exploring the Past and Current Landscape of Biomarker-Driven Clinical Trials Through Large Language Models First, we pretrained the encoder of a transformer-based network using a self-supervised ...

Abstract: The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule objects ...

This capstone project develops a machine learning pipeline to classify coding genetic variants as pathogenic versus benign using pretrained protein language model embeddings (ESM2). The work supports ...

Abstract: Ovarian cancer is one of the most common and highly lethal gynecological malignancies, and its early diagnosis and accurate subtyping are of great clinical significance. Whole-slide images ...