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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...

Robot-Assisted Gait Training in Older Patients with Comorbid Conditions: A Pilot Study.

Experimental aging research
PURPOSE: This study aimed to evaluate the efficacy of robot-assisted gait training (RAGT) in older patients with neurological gait disorder accompanied by various comorbidities.

Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT.

PloS one
PURPOSE: This study aims to explore the potential of non-contrast abdominal CT radiomics and deep learning models in accurately diagnosing fatty liver.

Table tennis coaching system based on a multimodal large language model with a table tennis knowledge base.

PloS one
UNLABELLED: Table tennis is one of the most popular sports in the world, and it plays a positive role in the overall development of people's physical and mental health. This study develops an AI table tennis coaching system using a Multimodal Large L...

Deep learning based screening model for hip diseases on plain radiographs.

PloS one
INTRODUCTION: The interpretation of plain hip radiographs can vary widely among physicians. This study aimed to develop and validate a deep learning-based screening model for distinguishing normal hips from severe hip diseases on plain radiographs.

Optimising test intervals for individuals with type 2 diabetes: A machine learning approach.

PloS one
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...

Objectifying aesthetic outcomes following face transplantation - the AI research metrics model (CAARISMA® ARMM).

Journal of stomatology, oral and maxillofacial surgery
BACKGROUND: Face transplantation (FT) offers a reconstructive option for patients with severe facial disfigurements by restoring both function and appearance. Aesthetic outcomes, which are crucial to psychological well-being and social reintegration,...

Using ChatGPT-4 in visual field test assessment.

Clinical & experimental optometry
CLINICAL RELEVANCE: Visual field testing is essential in the diagnosis and management of various ophthalmic diseases, particularly glaucoma. Integrating ChatGPT-4 into the interpretation of these tests has the potential to aid clinical decision makin...

Association of visceral fat obesity with structural change in abdominal organs: fully automated three-dimensional volumetric computed tomography measurement using deep learning.

Abdominal radiology (New York)
The purpose of this study was to explore the association between structural changes in abdominal organs and visceral fat obesity (VFO) using a fully automated three-dimensional (3D) volumetric computed tomography (CT) measurement method based on deep...

Assessing ChatGPT Responses to Frequently Asked Patient Questions in Reconstructive Urology.

Urology practice
INTRODUCTION: Artificial intelligence (such as Chat Generative Pretrained Transformer [ChatGPT]) augments patient education on medical topics, including reconstructive surgery. In this study, we assess the information, misinformation, and readability...