AIMC Topic: Adolescent
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A cohort study of predictors of short-term nonfatal suicidal and self-harm events among individuals with mental health disorders treated in the emergency department.
Journal of psychiatric research
Apr 22, 2025
BACKGROUND: Patients presenting to emergency departments (EDs) for mental health problems have an elevated short-term risk of repeat ED visits, subsequent hospitalization, and suicide.
Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic.
Scientific reports
Apr 22, 2025
Suicide causes over 700,000 deaths annually worldwide. Mental disorders are closely linked to suicidal ideation, but predicting suicide remains complex due to the multifaceted nature of contributing factors. Traditional assessment tools often fail to...
Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.
Computer methods and programs in biomedicine
Apr 20, 2025
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...
Integrating Machine Learning and Follow-Up Variables to Improve Early Detection of Hepatocellular Carcinoma in Tyrosinemia Type 1: A Multicenter Study.
International journal of molecular sciences
Apr 18, 2025
Hepatocellular carcinoma (HCC) is a major complication of tyrosinemia type 1 (HT-1), an inborn error of metabolism affecting tyrosine catabolism. The risk of HCC is higher in late diagnoses despite treatment. Alpha-fetoprotein (AFP) is widely used to...
Alanine Transaminase
Male
Tyrosinemias
Follow-Up Studies
Middle Aged
Humans
Child, Preschool
Early Detection of Cancer
Infant, Newborn
Infant
alpha-Fetoproteins
Machine Learning
Child
Young Adult
Adolescent
Alkaline Phosphatase
Retrospective Studies
Liver Neoplasms
Adult
Female
Carcinoma, Hepatocellular
Biomarkers, Tumor
Longitudinal Studies
MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d'Ivoire.
Malaria journal
Apr 18, 2025
BACKGROUND: In sub-Saharan Africa, Plasmodium falciparum is the most prevalent species of malaria parasites. In endemic areas, malaria is mainly diagnosed using microscopy or rapid diagnostic tests (RDTs), which have limited sensitivity, and microsco...
A machine learning approach to investigate the role of fear of pain, personal experience, and vicarious learning in dental anxiety.
BMC oral health
Apr 18, 2025
BACKGROUND: Dental anxiety is a pervasive problem worldwide, leading to avoidance of dental care, resulting in oral health problems and impacting daily life through social withdrawal and work absenteeism. Addressing this fear is an important public h...
Joint resting state and structural networks characterize pediatric bipolar patients compared to healthy controls: a multimodal fusion approach.
NeuroImage
Apr 17, 2025
Pediatric bipolar disorder (PBD) is a highly debilitating condition, characterized by alternating episodes of mania and depression, with intervening periods of remission. Limited information is available about the functional and structural abnormalit...
Assessment of AI-accelerated T2-weighted brain MRI, based on clinical ratings and image quality evaluation.
European journal of radiology
Apr 16, 2025
OBJECTIVE: To compare clinical ratings and signal-to-noise ratio (SNR) measures of a commercially available Deep Learning-based MRI reconstruction method (T2) against conventional T2- turbo spin echo brain MRI (T2).
Calibration and Validation of Machine Learning Models for Physical Behavior Characterization: Protocol and Methods for the Free-Living Physical Activity in Youth (FLPAY) Study.
JMIR research protocols
Apr 16, 2025
BACKGROUND: Wearable activity monitors are increasingly used to characterize physical behavior. The development and validation of these characterization methods require criterion-labeled data typically collected in a laboratory or simulated free-livi...
Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose.
BMC research notes
Apr 15, 2025
OBJECTIVE: Sex determination is an important parameter for personal identification in forensic and medico-legal examinations. The study aims at predicting sex accuracy from different parameters of ear and nose by using a novel approach of Machine Lea...
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