Self-Normalizing Multi-Omics Neural Network for Pan-Cancer Prognostication
Abstract Prognostic markers such as overall survival (OS) and tertiary lymphoid structure (TLS) ratios, alongside diagnostic signatures like primary cancer-type…
Machine learning
Interpretable graph Kolmogorov–Arnold networks for multi-cancer classification and biomarker identification using multi-omics data
Abstract The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational…
Molecular function validation and prognostic value analysis of the cuproptosis-related gene ferredoxin 1 in papillary thyroid carcinoma
Abstract Supplementary Information: The online version contains supplementary material available at 10.1038/s41598-025-11151-2. Article type: Research Article Keywords: Papillary thyroid carcinoma,…
Machine Learning-Based Prognostic Signature in Breast Cancer: Regulatory T Cells, Stemness, and Deep Learning for Synergistic Drug Discovery
Abstract Regulatory T cells (Tregs) have multiple roles in the tumor microenvironment (TME), which maintain a balance between autoimmunity and…
Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer
Abstract Background: Thyroid cancer (THCA) exhibits high molecular heterogeneity, posing challenges for precise prognosis and personalized therapy. Most existing models…
The Emerging Clinical Relevance of Artificial Intelligence, Data Science, and Wearable Devices in Headache: A Narrative Review
Abstract This narrative review introduces key concepts in artificial intelligence (AI), data science, and wearable devices aimed at headache clinicians…
Powdery mildew resistance prediction in Barley (Hordeum Vulgare L) with emphasis on machine learning approaches
Abstract By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley…
Recent advances (2022–2024) in eye-tracking for Parkinson’s disease: a promising tool for diagnosing and monitoring symptoms
Abstract Introduction: Parkinson’s disease (PD) is one of the most prevalent neurodegenerative disorders, characterized by both motor and non-motor symptoms,…
Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005–2020
Abstract Overactive bladder (OAB), a prevalent condition characterized by urgency and nocturia, imposes significant burdens on both quality of life…
Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods
Abstract Introduction: MicroRNAs (miRNAs) regulate gene expression and play an important role in carcinogenesis through complex interactions with messenger RNAs…