AIMC Topic: Adolescent

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Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study.

Skeletal radiology
OBJECTIVES: Some sarcomas are highly malignant, associated with high recurrence despite treatment. This multicenter study aimed to develop and validate a radiomics signature to estimate sarcoma progression-free survival (PFS).

Use of machine learning for simplification of University Personality Inventory (UPI).

Acta psychologica
BACKGROUND: Rapid diagnosis of mental health problems is crucial for college students. The University Personality Inventory (UPI) is a commonly used tools for assessing mental health in college students; however, it has certain limitations. This stud...

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain.

Neural networks : the official journal of the International Neural Network Society
In practice, collecting auxiliary labeled data with same feature space from multiple domains is difficult. Thus, we focus on the heterogeneous transfer learning to address the problem of insufficient sample sizes in neuroimaging. Viewing subjects, ti...

Employing machine learning models to predict pregnancy termination among adolescent and young women aged 15-24 years in East Africa.

Scientific reports
Pregnancy termination is still a sensitive and continuing public health issue due to several political, economic, religious, and social concerns. This study assesses the applications of machine learning models in the prediction of pregnancy terminati...

Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.

Archives of physical medicine and rehabilitation
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).

Multitask learning for automatic detection of meniscal injury on 3D knee MRI.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Magnetic resonance imaging (MRI) of the knee is the recommended diagnostic method before invasive arthroscopy surgery. Nevertheless, interpreting knee MRI scans is a time-consuming process that is vulnerable to inaccuracies and inconsistencies. We pr...

Machine Learning-based Prediction of Blood Stream Infection in Pediatric Febrile Neutropenia.

Journal of pediatric hematology/oncology
OBJECTIVES: This study aimed to develop machine learning (ML) prediction models for identifying bloodstream infection (BSI) and septic shock (SS) in pediatric patients with cancer who presenting febrile neutropenia (FN) at emergency department (ED) v...

Validation of an Artificial Intelligence-based Tool - The Screening Corneal Objective Risk of Ectasia Integrated into Anterion for Detection of Corneal Ectasia/Risk of Ectasia.

Middle East African journal of ophthalmology
PURPOSE: The purpose of this study was to validate the artificial intelligence-based Screening Corneal Objective Risk of Ectasia (SCORE) for the detection of corneal ectasia/risk of ectasia and to find the mean SCORE value in normal eyes.

Estimating Ground Reaction Forces from Gait Kinematics in Cerebral Palsy: A Convolutional Neural Network Approach.

Annals of biomedical engineering
PURPOSE: While gait analysis is essential for assessing neuromotor disorders like cerebral palsy (CP), capturing accurate ground reaction force (GRF) measurements during natural walking presents challenges, particularly due to variations in gait patt...