Latest AI and machine learning research in leukemia for healthcare professionals.
Background: Medical imaging, especially computed tomography and magnetic resonance imaging, is essen...
Rational design of covalent inhibitors requires simultaneously optimizing multiple properties, such ...
BackgroundPredicting whether a treatment will demonstrate meaningful clinical benefit before committ...
Acute Myeloid Leukemia (AML) is one of the most life-threatening type of blood cancers, and its accu...
Machine learning in high-stakes domains such as healthcare requires not only strong predictive perfo...
Peripheral Blood transcriptome analysis evaluated the bulk transcript abundance (TA) covering all le...
Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and s...
In this study, we proposed a deep Swin-Vision Transformer-based transfer learning architecture for r...
Building virtual cells with generative models to simulate cellular behavior in silico is emerging as...
Social determinants of health (SDoH), the social, economic, and environmental conditions shaping hea...
Building virtual cells with generative models to simulate cellular behavior in silico is emerging as...
In clinical practice, crossmodal information including medical images and tabular data is essential ...
Causal models of cellular systems hold the promise to empower broad biological discovery, including ...
Estimating slide- and patch-level gene expression profiles from pathology images enables rapid and l...
Cell segmentation is a fundamental task in microscopy image analysis. Several foundation models for ...
Automated white blood cell (WBC) classification is essential for leukemia screening but remains chal...
De novo peptide design methods traditionally couple generation to 3D structure prediction, limiting ...
Automated white blood cell (WBC) classification is essential for leukemia screening but remains chal...
Lung cancer is a condition where there is abnormal growth of malignant cells that spread in an uncon...
Understanding non-genetic determinants of cell fate is critical for developing and improving cancer ...
We present HistoAtlas, a pan-cancer computational atlas that extracts 38 interpretable histomic feat...