AI Medical Compendium Topic:
Cross-Sectional Studies

Clear Filters Showing 691 to 700 of 1223 articles

Machine learning to predict distal caries in mandibular second molars associated with impacted third molars.

Scientific reports
Impacted mandibular third molars (M3M) are associated with the occurrence of distal caries on the adjacent mandibular second molars (DCM2M). In this study, we aimed to develop and validate five machine learning (ML) models designed to predict the occ...

Automatic segmentation of corneal deposits from corneal stromal dystrophy images via deep learning.

Computers in biology and medicine
BACKGROUND: Granular dystrophy is the most common stromal dystrophy. To perform automated segmentation of corneal stromal deposits, we trained and tested a deep learning (DL) algorithm from patients with corneal stromal dystrophy and compared its per...

Needs for re-intervention on restored teeth in adults: a practice-based study.

Clinical oral investigations
OBJECTIVES: Evaluate the need for re-intervention on dental coronal restorations in adults seen in a network of general dental practitioners (ReCOL).  MATERIALS AND METHODS: This observational, cross-sectional, multicenter study involved 40 practitio...

Digital phenotyping of sleep patterns among heterogenous samples of Latinx adults using unsupervised learning.

Sleep medicine
OBJECTIVE: This study aimed to identify sleep disturbance subtypes ("phenotypes") among Latinx adults based on objective sleep data using a flexible unsupervised machine learning technique.

Role of Robotics and Artificial Intelligence in Oral Health and Preventive Dentistry - Knowledge, Perception and Attitude of Dentists.

Oral health & preventive dentistry
PURPOSE: To assess the knowledge, attitude and perception of dentists (dental students, dental school graduates/interns, postgraduate dentists) of the role of robotics (R) and artificial intelligence (AI) in oral health and preventive dentistry. The ...

Digitalization of waste management: Insights from German private and public waste management firms.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Policymakers, practitioners, and scholars have long-lauded digital technologies, such as smart waste containers or artificial intelligence for material recognition and robotic automation, as key enablers to more effective and efficient waste manageme...

Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age-related macular degeneration.

Acta ophthalmologica
PURPOSE: This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) ...

Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.

Environmental pollution (Barking, Essex : 1987)
Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of o...

Prediction of absenteeism in public schools teachers with machine learning.

Revista de saude publica
OBJECTIVE: To predict the risk of absence from work due to morbidities of teachers working in early childhood education in the municipal public schools, using machine learning algorithms.