AIMC Topic: Neoplasms
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Compressed Representation of Extreme Learning Machine with Self-Diffusion Graph Denoising Applied for Dissecting Molecular Heterogeneity.
Journal of computational biology : a journal of computational molecular cell biology
Mar 19, 2025
Molecular heterogeneity exists in many biological systems, such as major malignancies or diverse cell populations. Clustering of gene expression profiles has been widely used to dissect molecular heterogeneity. One drawback common to most clustering ...
Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm.
Scientific reports
Mar 19, 2025
With the advancement of medical technology, a large amount of complex data on cancers is produced for diagnosing and treating cancers. However, not all this data is useful, as many features are redundant or irrelevant, which can reduce the accuracy o...
Unsupervised learning to identify symptom clusters in older adults undergoing chemotherapy.
Journal of geriatric oncology
Mar 14, 2025
INTRODUCTION: Unsupervised machine learning (ML) approaches such as clustering have not been commonly applied to patient-reported data. This study describes ML methods to explore and describe patient-reported symptom trajectories in older adults rece...
Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.
Nature communications
Mar 14, 2025
Genetic variants can affect protein function by driving aberrant subcellular localization. However, comprehensive analysis of how mutations promote tumor progression by influencing nuclear localization is currently lacking. Here, we systematically ch...
Integration of Photodiagnosis and Therapy Guided by Micro/Nanorobots.
Advanced materials (Deerfield Beach, Fla.)
Mar 13, 2025
Micro/Nanorobots(MNRs)integrated with phototherapy represent an emerging approach to cancer treatment and hold significant potential for addressing bacterial infections, neurological disorders, cardiovascular diseases, and related conditions. By leve...
Validation of OncoOrigin: An Integrative AI Tool for Primary Cancer Site Prediction with Graphical User Interface to Facilitate Clinical Application.
International journal of molecular sciences
Mar 13, 2025
Cancers of unknown primary (CUPs) represent a significant diagnostic and therapeutic challenge in the field of oncology. Due to the limitations of current diagnostic tools in these cases, novel approaches must be brought forward to improve treatment ...
Association between muscle mass assessed by an artificial intelligence-based ultrasound imaging system and quality of life in patients with cancer-related malnutrition.
Nutrition (Burbank, Los Angeles County, Calif.)
Mar 12, 2025
INTRODUCTION: Emerging evidence suggests that diminished skeletal muscle mass is associated with lower health-related quality of life (HRQOL) in individuals with cancer. There are no studies that we know of in the literature that use ultrasound syste...
UniSAL: Unified Semi-supervised Active Learning for histopathological image classification.
Medical image analysis
Mar 12, 2025
Histopathological image classification using deep learning is crucial for accurate and efficient cancer diagnosis. However, annotating a large amount of histopathological images for training is costly and time-consuming, leading to a scarcity of avai...
Unraveling the power of NAP-CNB's machine learning-enhanced tumor neoantigen prediction.
eLife
Mar 11, 2025
In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) using a machine learning-based platform called NAP-CNB. Unlike other TNA predictors, NAP-CNB leverag...
Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.
International journal of molecular sciences
Mar 10, 2025
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...
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