Latest AI and machine learning research in oncology/hematology for healthcare professionals.
The interaction between T-cell receptors (TCRs) with the peptide-bound major histocompatibility complex (MHC) intricately impacts the functional specificity of T-cell-mediated adaptive immune response. Consequently, implication in immunotherapy has contributed to the ever-growing computational methods for TCR recognition, which have recently attracted structure-based approaches due to advancements...
Cancer driver mutations shape the tumor microenvironment (TME), yet whether TME composition alone can predict genotype has not been systematically evaluated across cancers with external validation. We trained machine learning models to predict driver mutation status from TME cell-type composition signatures derived from bulk transcriptomes. Tissue-specific TME signatures (22-28 programs per cancer...
Standard Test-Time Adaptation (TTA) methods typically treat inference as a blind optimization task, applying generic objectives to all or filtered tes...
Early detection of myometrial invasion is critical for the staging and life-saving management of endometrial carcinoma (EC), a prevalent global malign...
Immunotherapy with immune checkpoint inhibitors and immunotherapy combined with chemotherapy have represented promising treatments for NSCLC patients ...
Understanding spatial organization of cells is critical for deciphering tissue function and disease. Single-cell RNA-sequencing (scRNA-seq) profiles t...
Background: Current risk stratification for Ewing sarcoma relies heavily on clinical factors such as metastatic status, failing to capture histologic ...
We introduce a workflow that integrates BioEmu-generated conformational ensemble with physics-based molecular simulations and Markov State Models to s...
Radiomics and deep learning both offer powerful tools for quantitative medical imaging, but most existing fusion approaches only leverage global radio...
Objective: This study investigates whether incorporating physiological coupling concepts into neural network design can support stable and interpretab...
Triple-negative breast cancer (TNBC) is an aggressive subtype that lacks effective targeted therapies. This study aimed to identify robust prognostic ...
Primary central nervous system lymphoma (PCNSL) is a subtype of diffuse large B-cell lymphoma (DLBCL) with confined CNS growth. We evaluated tumor mic...
Protein structure prediction using deep learning has revolutionized protein design. Yet, our understanding of protein function remains a key limitatio...
Single-cell RNA sequencing enables high-resolution characterization of cellular heterogeneity, yet integrating datasets from diverse sources remains c...
Skin cancer can be life-threatening if not diagnosed early, a prevalent yet preventable disease. Globally, skin cancer is perceived among the finest p...
Alternative splicing is a core determinant of cell-type-specific gene expression in humans, and its dysregulation contributes to many diseases includi...
Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and physical health. Animal studies indicate that DNA me...
Computed Tomography (CT) is one of the largest contributors to radiation exposure from medical imaging, which can induce DNA damage and increase cance...
Understanding how perturbations influence gene function in a tissue-specific manner is key to uncovering novel drug targets. However, current computat...
The recurrence rate following complete surgical resection of primary non-small cell lung cancer is as high as 55%, yet no approach currently exists to...