AIMC Topic: Female

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A quantitative SVM approach potentially improves the accuracy of magnetic resonance spectroscopy in the preoperative evaluation of the grades of diffuse gliomas.

NeuroImage. Clinical
OBJECTIVES: To investigate the association between proton magnetic resonance spectroscopy (H-MRS) metabolic features and the grade of gliomas, and to establish a machine-learning model to predict the glioma grade.

Predicting childhood obesity using electronic health records and publicly available data.

PloS one
BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. ...

Novel pediatric-automated respiratory score using physiologic data and machine learning in asthma.

Pediatric pulmonology
OBJECTIVES: Manual clinical scoring systems are the current standard used for acute asthma clinical care pathways. No automated system exists that assesses disease severity, time course, and treatment impact in pediatric acute severe asthma exacerbat...

Artificial Neural Network Learns Clinical Assessment of Spasticity in Modified Ashworth Scale.

Archives of physical medicine and rehabilitation
OBJECTIVE: To propose an artificial intelligence (AI)-based decision-making rule in modified Ashworth scale (MAS) that draws maximum agreement from multiple human raters and to analyze how various biomechanical parameters affect scores in MAS.

Automated and accurate quantification of subcutaneous and visceral adipose tissue from magnetic resonance imaging based on machine learning.

Magnetic resonance imaging
Accurate measuring of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) is vital for the research of many diseases. The localization and quantification of SAT and VAT by computed tomography (CT) expose patients to harmful ionizing r...

Evaluate driver response to active warning system in level-2 automated vehicles.

Accident; analysis and prevention
As vehicles with automated functions become more prevalent on U.S. roadways, maintaining driver attention while the vehicle is engaged in automation will be an important consideration for safe operation of these vehicles. The objective of this paper ...

Machine learning accurately classifies age of toddlers based on eye tracking.

Scientific reports
How people extract visual information from complex scenes provides important information about cognitive processes. Eye tracking studies that have used naturalistic, rather than highly controlled experimental stimuli, reveal that variability in looki...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

ALTEX
Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's discomfort, distress and pain, while ensuring that scientific objectives are reached. Yet, lack of commonly agreed methodology and heterogeneity of cut-off...

Diagnosis of pain in the right iliac fossa. A new diagnostic score based on Decision-Tree and Artificial Neural Network Methods.

Cirugia espanola
INTRODUCTION: Pain in the right iliac fossa (RIF) continues to pose diagnostic challenges. The objective of this study is the development of a RIF pain diagnosis model based on classification trees of type CHAID (Chi-Square Automatic Interaction Dete...