INTRODUCTION: Rapid identification of individuals developing a psychotic spectrum disorder (PSD) is crucial because untreated psychosis is associated with poor outcomes and decreased treatment response. Lack of recognition of early psychotic symptoms...
BACKGROUND: Delayed breastfeeding initiation is a significant public health concern, and reducing the proportion of delayed breastfeeding initiation in East Africa is a key strategy for lowering the Child Mortality rate. However, there is limited evi...
BACKGROUND: Depression is very prevalent in middle-aged and older smokers. Therefore, we aimed to identify the risk of depression among middle-aged and older adults with frequent and infrequent nicotine use, as this is quite necessary for supporting ...
BACKGROUND: Small clinics are important in providing health care in local communities. Accurately predicting their closure would help manage health care resource allocation. There have been few studies on the prediction of clinic closure using machin...
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Aug 29, 2024
European journal of cancer (Oxford, England : 1990)
Aug 25, 2024
IMPORTANCE: Convolutional neural networks (CNN) have shown performance equal to trained dermatologists in differentiating benign from malignant skin lesions. To improve clinicians' management decisions, additional classifications into diagnostic cate...
Household water treatment (HWT) is recommended when safe drinking water is limited. To understand determinants of HWT adoption, we conducted a cross-sectional survey with 650 households across different regions in Haiti. Data were collected on 71 dem...
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Aug 17, 2024
OBJECTIVE: To assess the feasibility of using artificial intelligence (AI) to improve readability of online cataract surgery patient education materials (PEMs) in English and Spanish.
OBJECTIVES: This study aimed to train a 3D U-Net convolutional neural network (CNN) for mandible and lower dentition segmentation from cone-beam computed tomography (CBCT) scans.
PURPOSE: This cross-sectional study assessed a generative artificial intelligence platform to automate the creation of accurate, appropriate, and compelling social media (SoMe) posts from urological journal articles.