AIMC Topic: Machine Learning

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Development and validation of prediction models for nosocomial infection and prognosis in hospitalized patients with cirrhosis.

Antimicrobial resistance and infection control Aug 7, 2024
BACKGROUND: Nosocomial infections (NIs) frequently occur and adversely impact prognosis for hospitalized patients with cirrhosis. This study aims to develop and validate two machine learning models for NIs and in-hospital mortality risk prediction.
Hospital Mortality Liver Cirrhosis Area Under Curve Cross Infection Aged Male Middle Aged Humans Risk Assessment Prognosis Machine Learning Female Algorithms Risk Factors Hospitalization
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Solving the puzzle of quality of life in cancer: integrating causal inference and machine learning for data-driven insights.

Health and quality of life outcomes Aug 7, 2024
BACKGROUND: Understanding the determinants of global quality of life in cancer patients is crucial for improving their overall well-being. While correlations between various factors and quality of life have been established, the causal relationships ...
Neoplasms Quality of Life Surveys and Questionnaires Causality Aged Adult Male Middle Aged Humans Machine Learning Retrospective Studies Female
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Contrastive machine learning reveals Parkinson's disease specific features associated with disease severity and progression.

Communications biology Aug 7, 2024
Parkinson's disease (PD) exhibits heterogeneity in terms of symptoms and prognosis, likely due to diverse neuroanatomical alterations. This study employs a contrastive deep learning approach to analyze Magnetic Resonance Imaging (MRI) data from 932 P...
Female Aged Male Middle Aged Disease Progression Humans Machine Learning Biomarkers Brain Severity of Illness Index Deep Learning Magnetic Resonance Imaging Parkinson Disease
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Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

Journal of sports sciences Aug 7, 2024
The purpose of this study was to test whether a machine learning model can accurately predict VO across different exercise intensities by combining muscle oxygen (MO) with heart rate (HR). Twenty young highly trained athletes performed the following ...
Male Oxygen Consumption Humans Adolescent Exercise Test Machine Learning Muscle, Skeletal Heart Rate Female Oxygen Bicycling Young Adult
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Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care Aug 6, 2024
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.
Aged Male Middle Aged Cerebral Hemorrhage Seizures Outcome Assessment, Health Care Hematoma Glasgow Coma Scale Humans Machine Learning Phenotype Female
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Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.

Journal of applied gerontology : the official journal of the Southern Gerontological Society Aug 6, 2024
This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...
Female Risk Factors Aged Aged, 80 and over Humans Machine Learning Algorithms Prospective Studies Cognitive Dysfunction Longitudinal Studies Frailty Frail Elderly Linear Models Male Middle Aged Risk Assessment China
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Do machine learning methods improve prediction of ambient air pollutants with high spatial contrast? A systematic review.

Environmental research Aug 6, 2024
BACKGROUND & OBJECTIVE: The use of machine learning for air pollution modelling is rapidly increasing. We conducted a systematic review of studies comparing statistical and machine learning models predicting the spatiotemporal variation of ambient ni...
Soot Air Pollutants Air Pollution Particulate Matter Nitrogen Dioxide Machine Learning Environmental Monitoring
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Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 6, 2024
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...
Humans Machine Learning Decision Support Techniques Retrospective Studies Tomography, X-Ray Computed Clinical Decision-Making Female Predictive Value of Tests Ischemic Stroke Radiographic Image Interpretation, Computer-Assisted Infarction, Middle Cerebral Artery Middle Aged Risk Factors Risk Assessment Aged Thrombectomy Time Factors Aged, 80 and over Medical Futility Male Treatment Outcome
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Machine Learning Using Template-Based-Predicted Structure of Haemagglutinin Predicts Pathogenicity of Avian Influenza.

Journal of microbiology and biotechnology Aug 6, 2024
Deep learning presents a promising approach to complex biological classifications, contingent upon the availability of well-curated datasets. This study addresses the challenge of analyzing three-dimensional protein structures by introducing a novel ...
Computational Biology Principal Component Analysis Neural Networks, Computer Neuraminidase Machine Learning Hemagglutinin Glycoproteins, Influenza Virus Influenza in Birds Genome, Viral Algorithms Hemagglutinins Birds Animals Influenza A virus Deep Learning
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Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models.

Journal of hazardous materials Aug 6, 2024
This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as air fresheners, fragrances, and anti-fogging agents submitted to K-REACH using machine learning models. We manually curated inhalation toxicity data ba...
Household Products Organisation for Economic Co-Operation and Development Guidelines as Topic Inhalation Exposure Humans Toxicity Tests Machine Learning Consumer Product Safety
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