AIMC Topic: Adolescent

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Semiology Extraction and Machine Learning-Based Classification of Electronic Health Records for Patients With Epilepsy: Retrospective Analysis.

JMIR medical informatics
BACKGROUND: Obtaining and describing semiology efficiently and classifying seizure types correctly are crucial for the diagnosis and treatment of epilepsy. Nevertheless, there exists an inadequacy in related informatics resources and decision support...

Artificial Intelligence-Driven Skin Aging Simulation as a Novel Skin Cancer Prevention.

Dermatology (Basel, Switzerland)
INTRODUCTION: Skin cancer, a prevalent cancer type among fair-skinned patients globally, poses a relevant public health concern due to rising incidence rates. Ultraviolet (UV) radiation poses a major risk factor for skin cancer. However, intentional ...

Real-World evaluation of an AI triaging system for chest X-rays: A prospective clinical study.

European journal of radiology
Chest X-rays (CXRs) are crucial for diagnosing and managing lung conditions. While CXR is a common and cost-effective diagnostic tool, interpreting the high volume of CXRs is challenging due to workforce limitations. Artificial intelligence (AI) offe...

Federated learning-based prediction of depression among adolescents across multiple districts in China.

Journal of affective disorders
Depression in adolescents is a serious mental health condition that can affect their emotional and social well-being. Detailed understanding of depression patterns and status of depressive symptoms in adolescents could help identify early interventio...

Acceptability of artificial intelligence in dental radiology among patients in India: are we ready for this revolution?

Oral radiology
OBJECTIVE: In recent times, artificial Intelligence (AI) has gained popularity in medical as well as dental radiology. Studies have been conducted among medical and dental students and professionals about the knowledge and understanding towards AI. T...

Federated learning and deep learning framework for MRI image and speech signal-based multi-modal depression detection.

Computational biology and chemistry
Adolescence is a significant period for developing skills and knowledge and learning about managing relationships and emotions by gathering attributes for maturity. Recently, Depression arises as a common mental health issue in adolescents and this a...

Predicting criminal offence in adolescents who exhibit antisocial behaviour: a machine learning study using data from a large randomised controlled trial of multisystemic therapy.

European child & adolescent psychiatry
INTRODUCTION: Accurate prediction of short-term offending in young people exhibiting antisocial behaviour could support targeted interventions. Here we develop a set of machine learning (ML) models that predict offending status with good accuracy; fu...

A new scoring in differential diagnosis: multisystem inflammatory syndrome or adenovirus infection?

Turkish journal of medical sciences
BACKGROUND/AIM: Differentiating multisystem inflammatory syndrome in children (MIS-C) from adenovirus infection (AI) can be challenging due to similar clinical and laboratory findings. This study aimed to identify distinguishing characteristics and d...

Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control.

Predicting the Risk of Maxillary Canine Impaction Based on Maxillary Measurements Using Supervised Machine Learning.

Orthodontics & craniofacial research
OBJECTIVES: To predict palatally impacted maxillary canines based on maxilla measurements through supervised machine learning techniques.