AIMC Topic: Adolescent

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Electrocardiogram-Based Deep Learning to Predict Mortality in Repaired Tetralogy of Fallot.

JACC. Clinical electrophysiology
BACKGROUND: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to predict mortality in adults with acquired cardiovascular diseases. However, its application to the growing repaired tetralogy of Fallot (rTOF) populatio...

DentAge: Deep learning for automated age prediction using panoramic dental X-ray images.

Journal of forensic sciences
Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep-learning model for automated age prediction using panoramic dental X-ray images. DentAge was t...

Investigating the mechanisms of internet gaming disorder and developing intelligent monitoring models using artificial intelligence technologies: protocol of a prospective cohort.

BMC public health
BACKGROUND: Internet gaming disorder (IGD), recognized by the World Health Organization (WHO), significantly impacts adolescent mental and physical health. With a global prevalence of 3.05%, rates are higher in Asia, especially among adolescents and ...

Machine learning algorithm for predicting seizure control after temporal lobe resection using peri-ictal electroencephalography.

Scientific reports
Brain resection is curative for a subset of patients with drug resistant epilepsy but up to half will fail to achieve sustained seizure freedom in the long term. There is a critical need for accurate prediction tools to identify patients likely to ha...

Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.

JMIR mental health
BACKGROUND: The application of artificial intelligence (AI) to health and health care is rapidly increasing. Several studies have assessed the attitudes of health professionals, but far fewer studies have explored the perspectives of patients or the ...

Automated linguistic analysis in youth at clinical high risk for psychosis.

Schizophrenia research
Identifying individuals at clinical high risk for psychosis (CHRP) is crucial for preventing psychosis and improving the prognosis for schizophrenia. Individuals at CHR-P may exhibit mild forms of formal thought disorder (FTD), making it possible to ...

Machine learning-based discrimination of unipolar depression and bipolar disorder with streamlined shortlist in adolescents of different ages.

Computers in biology and medicine
BACKGROUND: Variations in symptoms and indistinguishable depression episodes of unipolar depression (UD) and bipolar disorder (BD) make the discrimination difficult and time-consuming. For adolescents with high disease prevalence, an efficient diagno...

Quality of birth care and risk factors of length of stay after birth: A machine learning approach.

The journal of obstetrics and gynaecology research
AIM: Length of stay (LOS) is an outcome measure and is assumed to be related to quality. The objective of this study is to examine the quality of birth care and risk factors associated with LOS after birth.

Diagnostic accuracy of artificial intelligence-assisted caries detection: a clinical evaluation.

BMC oral health
OBJECTIVE: This clinical study aimed to evaluate the practical value of integrating an AI diagnostic model into clinical practice for caries detection using intraoral images.

Machine learning-based evaluation of prognostic factors for mortality and relapse in patients with acute lymphoblastic leukemia: a comparative simulation study.

BMC medical informatics and decision making
BACKGROUND: Predicting mortality and relapse in children with acute lymphoblastic leukemia (ALL) is crucial for effective treatment and follow-up management. ALL is a common and deadly childhood cancer that often relapses after remission. In this stu...