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Development of a Wearable Sleeve-Based System Combining Polymer Optical Fiber Sensors and an LSTM Network for Estimating Knee Kinematics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...

Classification of fundus autofluorescence images based on macular function in retinitis pigmentosa using convolutional neural networks.

Japanese journal of ophthalmology
PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...

Prediction of adverse pregnancy outcomes using machine learning techniques: evidence from analysis of electronic medical records data in Rwanda.

BMC medical informatics and decision making
BACKGROUND: Despite substantial progress in maternal and neonatal health, Rwanda's mortality rates remain high, necessitating innovative approaches to meet health related Sustainable Development Goals (SDGs). By leveraging data collected from Electro...

Apriori algorithm based prediction of students' mental health risks in the context of artificial intelligence.

Frontiers in public health
INTRODUCTION: The increasing prevalence of mental health challenges among college students necessitates innovative approaches to early identification and intervention. This study investigates the application of artificial intelligence (AI) techniques...

Future pharmacy practitioners' insights towards integration of artificial intelligence in healthcare education: Preliminary findings from Karachi, Pakistan.

PloS one
UNLABELLED: In an evolutionary era of medical education, "Artificial intelligence" (AI) is applied to replicate human intellect, encompassing abilities, logical reasoning and effective problem-solving skills. Previous research has explored the attitu...

Machine learning for the early prediction of long-term cognitive outcome in autoimmune encephalitis.

Journal of psychosomatic research
BACKGROUND AND OBJECTIVE: Autoimmune encephalitis (AE) is an immune-mediated disease. Some patients experience persistent cognitive deficits despite receiving immunotherapy. We aimed to develop a prediction model for long-term cognitive outcomes in p...

A novel method for assessing cycling movement status: an exploratory study integrating deep learning and signal processing technologies.

BMC medical informatics and decision making
This study proposes a deep learning-based motion assessment method that integrates the pose estimation algorithm (Keypoint RCNN) with signal processing techniques, demonstrating its reliability and effectiveness.The reliability and validity of this m...

Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework.

IEEE journal of biomedical and health informatics
High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for localizing the seizure onset zone (SOZ) in patients with focal refractory epilepsy. Despite their clinical significance, HFO analysis is often compro...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

IEEE journal of biomedical and health informatics
Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk individuals, determining treatment needs, monitoring prevention and intervention efforts, and recruit...

Towards a latent space cartography of subjective experience in mental health.

Psychiatry and clinical neurosciences
AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and depth of such experiences. One persistent problem ...