AIMC Topic: Bayes Theorem

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Machine learning algorithms for the evaluation of risk by tick-borne pathogens in Europe.

Annals of medicine Sep 30, 2024
BACKGROUND: Tick-borne pathogens pose a major threat to human health worldwide. Understanding the epidemiology of tick-borne diseases to reduce their impact on human health requires models covering large geographic areas and considering both the abio...
Ticks Tick-Borne Diseases Humans Neural Networks, Computer Machine Learning Animals Algorithms Ecosystem Bayes Theorem Risk Assessment Ixodidae Europe Ixodes Dermacentor
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Predicting Intra- and Postpartum Hemorrhage through Artificial Intelligence.

Medicina (Kaunas, Lithuania) Sep 30, 2024
: Intra/postpartum hemorrhage stands as a significant obstetric emergency, ranking among the top five leading causes of maternal mortality. The aim of this study was to assess the predictive performance of four machine learning algorithms for the pre...
Postpartum Hemorrhage Support Vector Machine Predictive Value of Tests Artificial Intelligence Bayes Theorem Algorithms Prospective Studies Pregnancy Humans Female Adult Sensitivity and Specificity
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Proof of concept study on early forecasting of antimicrobial resistance in hospitalized patients using machine learning and simple bacterial ecology data.

Scientific reports Sep 30, 2024
Antibiotic resistance in bacterial pathogens is a major threat to global health, exacerbated by the misuse of antibiotics. In hospital practice, results of bacterial cultures and antibiograms can take several days. Meanwhile, prescribing an empirical...
Machine Learning Anti-Bacterial Agents Drug Resistance, Bacterial Hospitalization Microbial Sensitivity Tests Humans Bayes Theorem Neural Networks, Computer Bacteria France Bacterial Infections Proof of Concept Study
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Classification of mindfulness experiences from gamma-band effective connectivity: Application of machine-learning algorithms on resting, breathing, and body scan.

Computer methods and programs in biomedicine Sep 28, 2024
BACKGROUND AND OBJECTIVE: Practicing mindfulness is a mental process toward interoceptive awareness, achieving stress reduction and emotion regulation through brain-function alteration. Literature has shown that electroencephalography (EEG)-derived c...
Humans Machine Learning Respiration Algorithms Adult Mindfulness Male Stress, Psychological Brain Support Vector Machine Female Young Adult Bayes Theorem Electroencephalography Rest
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COVID-19 from symptoms to prediction: A statistical and machine learning approach.

Computers in biology and medicine Sep 28, 2024
During the COVID-19 pandemic, the analysis of patient data has become a cornerstone for developing effective public health strategies. This study leverages a dataset comprising over 10,000 anonymized patient records from various leading medical insti...
Bayes Theorem Child, Preschool Child Models, Statistical SARS-CoV-2 Aged Aged, 80 and over Adult Male Middle Aged Adolescent Machine Learning Pandemics COVID-19 Female Humans
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Analysis of influencing factors of traffic accidents on urban ring road based on the SVM model optimized by Bayesian method.

PloS one Sep 24, 2024
Based on small scale sample of accident data from specific scenarios, fully exploring the potential influencing factors of the severity of traffic accidents has become a key and effective research method. In order to analyze the factors mentioned abo...
Support Vector Machine Humans Bayes Theorem China Accidents, Traffic Cities
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Meta-learning as a bridge between neural networks and symbolic Bayesian models.

The Behavioral and brain sciences Sep 23, 2024
Meta-learning is even more broadly relevant to the study of inductive biases than Binz et al. suggest: Its implications go beyond the extensions to rational analysis that they discuss. One noteworthy example is that meta-learning can act as a bridge ...
Bayes Theorem Humans Neural Networks, Computer Learning
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Characterizing daily physical activity patterns with unsupervised learning via functional mixture models.

Journal of behavioral medicine Sep 21, 2024
Physical inactivity is a significant public health concern. Consideration of inter-individual variations in physical activity (PA) trends can provide additional information about the groups under study to aid intervention design. This study aims to i...
Cluster Analysis Unsupervised Machine Learning Bayes Theorem Accelerometry Male Middle Aged Exercise Humans Female Phenotype Aged Sedentary Behavior Young Adult Adult
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Development of a Natural Language Processing (NLP) model to automatically extract clinical data from electronic health records: results from an Italian comprehensive stroke center.

International journal of medical informatics Sep 19, 2024
INTRODUCTION: Data collection often relies on time-consuming manual inputs, with a vast amount of information embedded in unstructured texts such as patients' medical records and clinical notes. Our study aims to develop a pipeline that combines acti...
Humans Machine Learning Prognosis Male Middle Aged Natural Language Processing Ischemic Stroke Electronic Health Records Female Aged Bayes Theorem Data Mining Italy Stroke
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Machine learning approaches to evaluate heterogeneous treatment effects in randomized controlled trials: a scoping review.

Journal of clinical epidemiology Sep 19, 2024
BACKGROUND AND OBJECTIVES: Estimating heterogeneous treatment effects (HTEs) in randomized controlled trials (RCTs) has received substantial attention recently. This has led to the development of several statistical and machine learning (ML) algorith...
Treatment Outcome Randomized Controlled Trials as Topic Bayes Theorem Treatment Effect Heterogeneity Humans Machine Learning Algorithms
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