AIMC Topic: Female

Clear Filters Showing 15911 to 15920 of 29210 articles

Predicting changes in substance use following psychedelic experiences: natural language processing of psychedelic session narratives.

The American journal of drug and alcohol abuse
: Experiences with psychedelic drugs, such as psilocybin or lysergic acid diethylamide (LSD), are sometimes followed by changes in patterns of tobacco, opioid, and alcohol consumption. But, the specific characteristics of psychedelic experiences that...

Machine ​learning algorithms for claims data-based prediction of in-hospital mortality in patients with heart failure.

ESC heart failure
AIMS: Models predicting mortality in heart failure (HF) patients are often limited with regard to performance and applicability. The aim of this study was to develop a reliable algorithm to compute expected in-hospital mortality rates in HF cohorts o...

Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study.

Journal of medical Internet research
BACKGROUND: The use of artificial intelligence has revolutionized every area of life such as business and trade, social and electronic media, education and learning, manufacturing industries, medicine and sciences, and every other sector. The new ref...

Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non-muscle-invasive Bladder Cancer.

European urology oncology
Despite being standard tools for decision-making, the European Organisation for Research and Treatment of Cancer (EORTC), European Association of Urology (EAU), and Club Urologico Espanol de Tratamiento Oncologico (CUETO) risk groups provide moderate...

Natural language processing for the surveillance of postoperative venous thromboembolism.

Surgery
BACKGROUND: The objective of this study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes.

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Computers in biology and medicine
Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premature babies cared for in neonatal intensive care units (NICUs). Mortality risk prediction in this setting can greatly improve patient outcomes and reso...

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images.

Scientific reports
Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convo...

Gaining Insights Into Patient Satisfaction Through Interpretable Machine Learning.

IEEE journal of biomedical and health informatics
Patient satisfaction is a key performance indicator of patient-centered care and hospital reimbursement. To discover the major factors that affect patient experiences is considered as an effective way to formulate corrective actions. A patient during...

Predicting the Prognosis of MCI Patients Using Longitudinal MRI Data.

IEEE/ACM transactions on computational biology and bioinformatics
The aim of this study is to develop a computer-aided diagnosis system with a deep-learning approach for distinguishing "Mild Cognitive Impairment (MCI) due to Alzheimer's Disease (AD)" patients among a list of MCI patients. In this system we are usin...

Multi-View Mammographic Density Classification by Dilated and Attention-Guided Residual Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Breast density is widely adopted to reflect the likelihood of early breast cancer development. Existing methods of mammographic density classification either require steps of manual operations or achieve only moderate classification accuracy due to t...