AIMC Topic:
Young Adult

Clear Filters Showing 1151 to 1160 of 4442 articles

Predictive modelling of stress, anxiety and depression: A network analysis and machine learning study.

The British journal of clinical psychology
OBJECTIVE: This study assessed predictors of stress, anxiety and depression during the COVID-19 pandemic using a large number of demographic, COVID-19 context and psychological variables.

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...

EMG-based prediction of step direction for a better control of lower limb wearable devices.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control...

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...

Driver drowsiness is associated with altered facial thermal patterns: Machine learning insights from a thermal imaging approach.

Physiology & behavior
Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected ...

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...

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

Journal of neuroengineering and rehabilitation
BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking pro...