AIMC Topic: Adolescent

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Deep learning for 3D cephalometric landmarking with heterogeneous multi-center CBCT dataset.

PloS one
Cephalometric analysis is critically important and common procedure prior to orthodontic treatment and orthognathic surgery. Recently, deep learning approaches have been proposed for automatic 3D cephalometric analysis based on landmarking from CBCT ...

Self-help groups and opioid use disorder treatment: An investigation using a machine learning-assisted robust causal inference framework.

International journal of medical informatics
OBJECTIVES: This study investigates the impact of participation in self-help groups on treatment completion among individuals undergoing medication for opioid use disorder (MOUD) treatment. Given the suboptimal adherence and retention rates for MOUD,...

Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning.

Autism research : official journal of the International Society for Autism Research
Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter bra...

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker.

Nature aging
Short-term mortality risk, which is indicative of individual frailty, serves as a marker for aging. Previous age clocks focused on predicting either chronological age or longer-term mortality. Aging clocks predicting short-term mortality are lacking ...

Deep learning models for predicting the survival of patients with medulloblastoma based on a surveillance, epidemiology, and end results analysis.

Scientific reports
Medulloblastoma is a malignant neuroepithelial tumor of the central nervous system. Accurate prediction of prognosis is essential for therapeutic decisions in medulloblastoma patients. We analyzed data from 2,322 medulloblastoma patients using the SE...

Estimating mandibular growth stage based on cervical vertebral maturation in lateral cephalometric radiographs using artificial intelligence.

Progress in orthodontics
INTRODUCTION: Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to estimate the mandibular growth stage based on cervical vertebral maturat...

Multicenter validation of an artificial intelligence (AI)-based platform for the diagnosis of acute appendicitis.

Surgery
BACKGROUND: The current scores used to help diagnose acute appendicitis have a "gray" zone in which the diagnosis is usually inconclusive. Furthermore, the universal use of CT scanning is limited because of the radiation hazards and/or limited resour...

Public perceptions of artificial intelligence in healthcare: ethical concerns and opportunities for patient-centered care.

BMC medical ethics
BACKGROUND: In an effort to improve the quality of medical care, the philosophy of patient-centered care has become integrated into almost every aspect of the medical community. Despite its widespread acceptance, among patients and practitioners, the...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychiatry research
Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a prot...

A deep learning-based algorithm for automatic detection of perilunate dislocation in frontal wrist radiographs.

Hand surgery & rehabilitation
This study proposes a Deep Learning algorithm to automatically detect perilunate dislocation in anteroposterior wrist radiographs. A total of 374 annotated radiographs, 345 normal and 29 pathological, of skeletally mature adolescents and adults aged ...