AIMC Topic: Female

Clear Filters Showing 15251 to 15260 of 29210 articles

: An investigation of public trust in South Korea.

Journal of communication in healthcare
BACKGROUND: Humanoid robots with artificial intelligence have been implemented in many healthcare facilities including hospitals, nursing homes, and many others. Due to the development of technology and the increasing use of humanoid robots, it is ex...

Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia.

Scientific reports
Artificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and nervous system. Several studies clarified its application in medicine. However, none has applied ANN to predict the efficacy of folic acid treatment ...

Using explainable machine learning to identify patients at risk of reattendance at discharge from emergency departments.

Scientific reports
Short-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance could help reduce the number of missed critical illnesses and could reduce avoidable utilization of em...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

Frontiers in endocrinology
fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does not guarantee success. Frozen embryo transfer (FET) is an important supplement to IVF-ET. Many factor...

Machine Learning for Predicting Motor Improvement After Acute Subcortical Infarction Using Baseline Whole Brain Volumes.

Neurorehabilitation and neural repair
Neuroimaging biomarkers are valuable predictors of motor improvement after stroke, but there is a gap between published evidence and clinical usage. In this work, we aimed to investigate whether machine learning techniques, when applied to a combin...

Study the Effect of the Risk Factors in the Estimation of the Breast Cancer Risk Score Using Machine Learning.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: Early prediction of breast cancer is one of the most essential fields of medicine. Many studies have introduced prediction approaches to facilitate the early prediction and estimate the future occurrence based on mammography periodic tests...

A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

JAMA network open
IMPORTANCE: The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by t...

Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records.

JAMA network open
IMPORTANCE: Detecting cognitive decline earlier among older adults can facilitate enrollment in clinical trials and early interventions. Clinical notes in longitudinal electronic health records (EHRs) provide opportunities to detect cognitive decline...

Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy.

JAMA network open
IMPORTANCE: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; however, many patients do not receive their recommended annual diabetic eye examinations, primarily owi...

Recycling diagnostic MRI for empowering brain morphometric research - Critical & practical assessment on learning-based image super-resolution.

NeuroImage
Preliminary studies have shown the feasibility of deep learning (DL)-based super-resolution (SR) technique for reconstructing thick-slice/gap diagnostic MR images into high-resolution isotropic data, which would be of great significance for brain res...