AIMC Topic: Machine Learning

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Focal cortical dysplasia detection by artificial intelligence using MRI: A systematic review and meta-analysis.

Epilepsy & behavior : E&B
PURPOSE: Focal cortical dysplasia (FCD) is a common cause of pharmacoresistant epilepsy. However, it can be challenging to detect FCD using MRI alone. This study aimed to review and analyze studies that used machine learning and artificial neural net...

Evaluating the National Early Warning Score (NEWS) in triage: A machine learning perspective.

International emergency nursing
BACKGROUND: The National Early Warning Score is widely used in Emergency Departments for triage, primarily to predict mortality. However, its effectiveness in assessing additional clinical outcomes relevant to triage, such as patient urgency and seve...

Predicting postoperative chronic opioid use with fair machine learning models integrating multi-modal data sources: a demonstration of ethical machine learning in healthcare.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Building upon our previous work on predicting chronic opioid use using electronic health records (EHR) and wearable data, this study leveraged the Health Equity Across the AI Lifecycle (HEAAL) framework to (a) fine tune the previously buil...

Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow Network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Heart disease prediction models often face stability challenges when applied to public datasets due to significant class imbalances, unlike the more balanced benchmark datasets. These imbalances can adversely affect various...

Machine learning in risk assessment for microvascular head and neck surgery.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: The integration of machine learning (ML) into microvascular surgery for the head and neck offers significant potential to enhance risk stratification, outcome prediction, and decision support. Traditional risk assessment methods are often li...

Farmers who implemented this, also implemented that: Use of association-rule-learning to improve biosecurity on dairies.

Preventive veterinary medicine
Biosecurity practices are the cornerstone of disease prevention and control programs. In Canada, their implementation is evaluated with a Risk Assessment Questionnaire (RAQ). Association Rule Learning (ARL) - a non-supervised machine learning algorit...

Machine Learning Models in the Detection of MB2 Canal Orifice in CBCT Images.

International dental journal
OBJECTIVES: The objective of the present study was to determine the accuracy of machine learning (ML) models in the detection of mesiobuccal (MB2) canals in axial cone-beam computed tomography (CBCT) sections.

MORPSO_ECD+ELM: A Unified Framework for Gene Selection and Cancer Classification.

IEEE journal of biomedical and health informatics
Gene selection and cancer classification are inherently multi-objective tasks that require balancing competing objectives, such as maximizing classification accuracy while minimizing irrelevant or redundant genes. Existing methods often optimize a si...

Cross- and Intra-Image Prototypical Learning for Multi-Label Disease Diagnosis and Interpretation.

IEEE transactions on medical imaging
Recent advances in prototypical learning have shown remarkable potential to provide useful decision interpretations associating activation maps and predictions with class-specific training prototypes. Such prototypical learning has been well-studied ...