AIMC Topic: Machine Learning

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[Establishing of mortality predictive model for elderly critically ill patients using simple bedside indicators and interpretable machine learning algorithms].

Zhonghua wei zhong bing ji jiu yi xue Feb 1, 2025
OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assess...
Female Aged Male Hospital Mortality APACHE Organ Dysfunction Scores Humans Machine Learning Algorithms Prognosis Retrospective Studies Critical Illness Intensive Care Units
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Prediction of Prostate Cancer Grades Using Radiomic Features.

Acta medica Okayama Feb 1, 2025
We developed a machine learning model for predicting prostate cancer (PCa) grades using radiomic features of magnetic resonance imaging. 112 patients diagnosed with PCa based on prostate biopsy between January 2014 and December 2021 were evaluated. L...
Radiomics Male Middle Aged Magnetic Resonance Imaging Machine Learning Retrospective Studies Aged Humans Prostatic Neoplasms Prostate-Specific Antigen Neoplasm Grading
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Constructing a Prognostic Model for Subtypes of Colorectal Cancer Based on Machine Learning and Immune Infiltration-Related Genes.

Journal of cellular and molecular medicine Feb 1, 2025
This study constructed a prognostic model combining machine learning-based immune infiltration-related genes in each CRC subtype. We used publicly accessible gene expression data and clinical information on colorectal cancer patients. Integrated bioi...
Computational Biology Gene Expression Regulation, Neoplastic DNA Copy Number Variations Male Gene Expression Profiling ROC Curve Gene Regulatory Networks Female Humans Colorectal Neoplasms Machine Learning Biomarkers, Tumor Algorithms Prognosis
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A systematic exposure-wide framework leveraging machine learning to identify multidomain exposure factors and their joint influence on cognitive function: Evidence from a neurological cohort.

Alzheimer's & dementia : the journal of the Alzheimer's Association Feb 1, 2025
INTRODUCTION: Cognitive decline has become a growing public concern, yet large-scale exposure data identifying the contributing factors remain limited.
Humans Machine Learning Female Risk Factors Life Style Neuropsychological Tests Aged Cognitive Dysfunction Male Cohort Studies Middle Aged Cognition Cluster Analysis
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Identification and Validation of Biomarkers in Metabolic Dysfunction-Associated Steatohepatitis Using Machine Learning and Bioinformatics.

Molecular genetics & genomic medicine Feb 1, 2025
BACKGROUND: The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing annually. MASH can progress to cirrhosis and hepatocellular carcinoma. However, the early diagnosis of MASH is challenging.
Fatty Liver Computational Biology Humans Machine Learning Biomarkers Animals Transcriptome Mice
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Predicting In-Hospital Fall Risk Using Machine Learning With Real-Time Location System and Electronic Medical Records.

Journal of cachexia, sarcopenia and muscle Feb 1, 2025
BACKGROUND: Hospital falls are the most prevalent and fatal event in healthcare, posing significant risks to patient health outcomes and institutional care quality. Real-time location system (RTLS) enables continuous tracking of patient location, pro...
Risk Assessment Hospitals Accidental Falls Female Risk Factors Hospitalization Aged Aged, 80 and over Male Middle Aged Machine Learning Retrospective Studies Electronic Health Records Republic of Korea Humans
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Tasselyzer, a machine learning method to quantify maize anther exertion, based on PlantCV.

The Plant journal : for cell and molecular biology Feb 1, 2025
Maize anthers emerge from male-only florets, a process that involves complex genetic programming and is affected by environmental factors. Quantifying anther exertion provides a key indicator of male fertility; however, traditional manual scoring met...
Machine Learning Genotype Zea mays Flowers Plant Breeding
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Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical data.

Alzheimer's & dementia : the journal of the Alzheimer's Association Feb 1, 2025
INTRODUCTION: Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, but its routine clinical use is limited by cost and accessibility barriers.
Biomarkers Brain Female Aged Humans Machine Learning Positron-Emission Tomography tau Proteins Male Magnetic Resonance Imaging Alzheimer Disease
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A Machine Learning Approach to Build and Evaluate a Molecular Prognostic Model for Endometrial Cancer Based on Tumour Microenvironment.

Journal of cellular and molecular medicine Feb 1, 2025
Endometrial cancer (EC) incidence and the associated tumour burden have increased globally. To build a molecular expression prognostic model based on the tumour microenvironment to guide personalised treatment using a machine learning approach. Two d...
Random Forest Endometrial Neoplasms Carcinoma, Endometrioid Retrospective Studies Middle Aged Female China Aged Nomograms Humans Aged, 80 and over Machine Learning Adult Tumor Microenvironment Biomarkers, Tumor
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Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.

Molecular informatics Feb 1, 2025
The human epidermal growth factor receptor 2 (HER2) is a critical oncogene implicated in the development of various aggressive cancers, particularly breast cancer. Discovering novel HER2 inhibitors is crucial for expanding therapeutic options for HER...
Humans Receptor, ErbB-2 Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Machine Learning Pharmacophore Molecular Docking Simulation Drug Discovery Antineoplastic Agents
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