Homologous recombination deficiency (HRD) is a critical biomarker for guiding targeted therapies, yet the full range of somatic alterations driving HRD across cancers remains incompletely characterized. Here, we present a tumor-agnostic machine learn...
Cancer remains one of the leading causes of global mortality, with lung, colon, skin, and breast cancers contributing significantly to the disease burden. Accurate and timely classification of histopathological images is critical for effective diagno...
BACKGROUND: Accurate multicancer classification constitutes a cornerstone of modern oncology, offering critical insights into diagnosis, therapeutic decision-making, and prognostication. Numerous existing approaches, however, remain restricted to lim...
Cancer is a complex disease characterized by uncontrolled cell growth, which can invade surrounding tissues and spread to distant organs. Most of the conventional methods of diagnosis fails to identify the primary organ when cancer spreads to other o...
Therapeutic resistance remains a defining challenge in oncology, limiting the durability of current therapies and contributing to disease relapse and poor patient outcomes. This review systematically integrates recent progress in understanding the mo...
BACKGROUND: The unstructured data of Chinese cancer electronic health records (EHRs) contains valuable medical expertise. Accurate medical entity recognition is crucial for building a medical-assisted decision system. Named entity recognition (NER) i...
BACKGROUND: Cancer survivorship is a complicated, chronic, and long-lasting experience, causing uncertainty and a wide range of physical and emotional health concerns. Due to the complexity of cancer, patients often seek out multiple sources of healt...
Protein therapeutics, particularly antibody-based therapies, have emerged as a cornerstone in modern disease treatment, offering key advantages over small molecules, including superior target specificity, longer half-life, and expanded target accessi...
A high-accuracy DNA-based cancer risk predictor was developed by blending Logistic Regression with Gaussian Naive Bayes, and its hyperparameters were optimized via grid search. Five cancer types (BRCA1, KIRC, COAD, LUAD, PRAD) were classified in a co...
Journal of chemical information and modeling
Nov 9, 2025
Integrating multiomics data for cancer subtype classification remains a critical yet challenging task due to the high dimensionality, heterogeneity, and limited interpretability of omics features. To address these limitations, we propose OmniCLIC, a ...
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