AIMC Topic: Machine Learning

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Exploring equine behavior: Wearable sensors data and explainable AI for enhanced classification.

Journal of equine veterinary science
Understanding equine behavior through advanced monitoring technologies is crucial for improving animal welfare, optimizing training strategies, and enabling early detection of health or stress-related issues. This study integrates wearable sensor dat...

Predicting host-pathogen interactions with machine learning algorithms: A scoping review.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
BACKGROUND: Diseases caused by pathogenic microorganisms pose a persistent global health challenge. Pathogens exploit host mechanisms through intricate molecular interactions. Understanding these host-pathogen interactions (HPIs), particularly protei...

A machine learning approach to differentiate stage IV from stage I colorectal cancer.

Computers in biology and medicine
BACKGROUND AND AIM: The stage at which Colorectal cancer (CRC) diagnosed is a crucial prognostic factor. Our study proposed a novel approach to aid in the diagnosis of stage IV CRC by utilizing supervised machine learning, analyzing clinical history,...

Uncovering hepatic transcriptomic and circulating proteomic signatures in MASH: A meta-analysis and machine learning-based biomarker discovery.

Computers in biology and medicine
BACKGROUND: Metabolic-associated steatohepatitis (MASH), the progressive form of metabolic-associated steatotic liver disease (MASLD), poses significant risks for liver fibrosis and cardiovascular complications. Despite extensive research, reliable b...

Immunohistochemistry and machine learning study of DNA replication-associated proteins in uterine epithelial tumors and precursor lesions.

Acta histochemica
Endometrioid adenocarcinoma (EA) has been on the increase in recent years in developed countries. Early detection of endometrioid adenocarcinoma in the endometrial corpus is crucial for patient prognosis and early treatment, although their distinctio...

A novel machine learning-based workflow to capture intra-patient heterogeneity through transcriptional multi-label characterization and clinically relevant classification.

Journal of biomedical informatics
OBJECTIVES: Patient classification into specific molecular subtypes is paramount in biomedical research and clinical practice to face complex, heterogeneous diseases. Existing methods, especially for gene expression-based cancer subtyping, often simp...

AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes.

SLAS technology
The performance and long-term health of athletes are significantly influenced by their cardiovascular resilience and associated risk factors. This study explores the innovative applications of Natural Language Processing (NLP) and Large Language Mode...

multiPI-TransBTS: A multi-path learning framework for brain tumor image segmentation based on multi-physical information.

Computers in biology and medicine
Brain Tumor Segmentation (BraTS) plays a critical role in clinical diagnosis, treatment planning, and monitoring the progression of brain tumors. However, due to the variability in tumor appearance, size, and intensity across different MRI modalities...

Machine learning-based detection and quantification of red blood cells in Cholistani cattle: A pilot study.

Research in veterinary science
This study presents the first account of using machine learning to detect and count normal and abnormal red blood cells (RBCs), including tear-drop cells and schistocytes, in Cholistani cattle from Pakistan. A Support Vector Machine (SVM) model was a...

Mitosis detection and classification for breast cancer diagnosis: What we know and what is next.

Computers in biology and medicine
Breast cancer is the second most deadly malignancy in women, behind lung cancer. Despite significant improvements in medical research, breast cancer is still accurately diagnosed with histological analysis. During this procedure, pathologists examine...