AIMC Topic: Machine Learning
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Tiny-objective segmentation for spot signs on multi-phase CT angiography via contrastive learning with dynamic-updated positive-negative memory banks.
Computers in biology and medicine
Jul 11, 2025
BACKGROUND AND OBJECTIVE: Presence of spot sign on CT Angiography (CTA) is associated with hematoma growth in patients with intracerebral hemorrhage. Measuring spot sign volume over time may aid to predict hematoma expansion. Due to the difficulties ...
Biomarker discovery for early breast cancer diagnosis using machine learning on transcriptomic data for biosensor development.
Computers in biology and medicine
Jul 11, 2025
Breast cancer is the second leading cause of female mortality globally. Effective diagnostic tools, such as biosensors that utilize reliable biomarkers, are essential for early detection, particularly in low-income countries. This study introduces a ...
Applications of machine learning for peripheral artery disease diagnosis and management: A systematic review.
Computers in biology and medicine
Jul 11, 2025
Peripheral artery disease (PAD) is a chronic condition caused by atherosclerosis, leading to arterial narrowing and obstruction, primarily in the lower extremities. This results in reduced blood flow and increases the risk of loss of limbs and mortal...
Emotion recognition in EEG Signals: Deep and machine learning approaches, challenges, and future directions.
Computers in biology and medicine
Jul 11, 2025
A crucial part of brain-computer interfaces is the use of electroencephalogram (EEG) signals for human emotion identification, which analyzes patterns of brain activity to determine the emotional state. This field of study is becoming increasingly im...
Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.
Microbiology spectrum
Jul 11, 2025
Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) to guide timely treatments. Traditional culture-based AST methods are slow, while existing whole-gen...
Enhancing Parkinson's disease prediction using meta-heuristic optimized machine learning models.
Personalized medicine
Jul 11, 2025
Parkinson's disease is a progressive neurological disorder affecting movement and cognition. Early detection is crucial but challenging with traditional methods. This study applies meta-heuristic optimization to enhance machine learning prediction mo...
Machine-Learning-Driven Discovery of -Phenylbenzenesulfonamides as a Novel Chemotype for Lactate Dehydrogenase A Inhibition with Anti-Pancreatic Cancer Activity.
Journal of medicinal chemistry
Jul 11, 2025
Lactate dehydrogenase A (LDHA) is a promising target for cancer therapy due to its crucial role in aerobic glycolysis. Despite extensive efforts, the structural diversity of LDHA inhibitors remains limited. Here, we utilized machine learning techniqu...
Machine Learning-Assisted Multimodal Early Screening of Lung Cancer Based on a Multiplexed Laser-Induced Graphene Immunosensor.
ACS nano
Jul 11, 2025
Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis. Early detection is critical for improving patient outcomes, yet current screening methods, such as low-dose computed tomography (CT), of...
Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Prospective Cohort Study.
Journal of medical Internet research
Jul 11, 2025
BACKGROUND: Given the challenges faced during percutaneous coronary intervention (PCI) for heavily calcified lesions, accurately predicting PCI success is crucial for enhancing patient outcomes and optimizing procedural strategies.
Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis.
JMIR cancer
Jul 11, 2025
BACKGROUND: Surgeons often face challenges in distinguishing between benign and malignant follicular thyroid neoplasms (FTNs), particularly small tumors, until diagnostic surgery is performed.
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