AIMC Topic: Female

Clear Filters Showing 26741 to 26750 of 29210 articles

Clinical machine learning predicting best stroke rehabilitation responders to exoskeletal robotic gait rehabilitation.

NeuroRehabilitation
BACKGROUND: Although clinical machine learning (ML) algorithms offer promising potential in forecasting optimal stroke rehabilitation outcomes, their specific capacity to ascertain favorable outcomes and identify responders to robotic-assisted gait t...

Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements.

Journal of Alzheimer's disease : JAD
BACKGROUND: Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack...

Hematological Indices and Genetic Variants of Premature Ovarian Insufficiency: Machine Learning Approaches.

Cardiovascular & hematological disorders drug targets
BACKGROUND: Premature Ovarian Insufficiency (POI) is associated with infertility. Little is known about the potential circulating biomarkers that could be used to predict POI. We have investigated the possible association between white and red blood ...

Updated Models of Alzheimer's Disease with Deep Neural Networks.

Journal of Alzheimer's disease : JAD
BACKGROUND: In recent years, researchers have focused on developing precise models for the progression of Alzheimer's disease (AD) using deep neural networks. Forecasting the progression of AD through the analysis of time series data represents a pro...

A new method for identification of traditional Chinese medicine constitution based on tongue features with machine learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The theory of Chinese medicine (TCM) constitution contributes to the optimisation of individualised healthcare programmes. However, at present, TCM constitution identification mainly relies on inefficient questionnaires with subjective bi...

Evaluation of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Using MR Images and Deep Learning Neural Networks.

Current medical imaging
INTRODUCTION: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using magnetic resonance (MR) imag...

New training, new attitudes: non-clinical components in Ukrainian medical PHDs training (regarding critical thinking, academic integrity and artificial intelligence use).

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: The paper studies the attitude to critical thinking, academic integrity and the Artificial Intelligence use of the Ukrainian medical PhD students.

Nonproliferative diabetic retinopathy dataset(NDRD): A database for diabetic retinopathy screening research and deep learning evaluation.

Health informatics journal
OBJECTIVES: In this article, we provide a database of nonproliferative diabetes retinopathy, which focuses on early diabetes retinopathy with hard exudation, and further explore its clinical application in disease recognition.

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep st...