AIMC Topic: Aged
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Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems rely on static visual representations for patients to perform motor imagination (MI) tasks, ...
Prognosis Prediction of Diffuse Large B-Cell Lymphoma in F-FDG PET Images Based on Multi-Deep-Learning Models.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical i...
Predicting Alzheimer's Disease Progression Using a Versatile Sequence-Length-Adaptive Encoder-Decoder LSTM Architecture.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Detecting Alzheimer's disease (AD) accurately at an early stage is critical for planning and implementing disease-modifying treatments that can help prevent the progression to severe stages of the disease. In the existing literature, diagnostic test ...
Estimating the Severity of Obstructive Sleep Apnea Using ECG, Respiratory Effort and Neural Networks.
IEEE journal of biomedical and health informatics
Jul 2, 2024
OBJECTIVE: wearable sensor technology has progressed significantly in the last decade, but its clinical usability for the assessment of obstructive sleep apnea (OSA) is limited by the lack of large and representative datasets simultaneously acquired ...
Optimizing drug therapy for older adults: shifting away from problematic polypharmacy.
Expert opinion on pharmacotherapy
Jul 2, 2024
INTRODUCTION: The accelerated discovery and production of pharmaceutical products has resulted in many positive outcomes. However, this progress has also contributed to problematic polypharmacy, one of the rapidly growing threats to public health in ...
Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.
NeuroImage. Clinical
Jul 2, 2024
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of...
Comparison of model feature importance statistics to identify covariates that contribute most to model accuracy in prediction of insomnia.
PloS one
Jul 2, 2024
IMPORTANCE: Sleep is critical to a person's physical and mental health and there is a need to create high performing machine learning models and critically understand how models rank covariates.
Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach.
Journal of imaging informatics in medicine
Jul 1, 2024
This study aims to evaluate an AI model designed to automatically classify skull fractures and visualize segmentation on emergent CT scans. The model's goal is to boost diagnostic accuracy, alleviate radiologists' workload, and hasten diagnosis, ther...
Prediction of molecular subclasses of uveal melanoma by deep learning using routine haematoxylin-eosin-stained tissue slides.
Histopathology
Jul 1, 2024
AIMS: Uveal melanoma has a high propensity to metastasize. Prognosis is associated with specific driver mutations and copy number variations, and these can only be obtained after genetic testing. In this study we evaluated the efficacy of patient out...
Tumor Suppressor Proteins
Eosine Yellowish-(YS)
Hematoxylin
RNA Splicing Factors
Deep Learning
Uveal Neoplasms
Humans
Staining and Labeling
Ubiquitin Thiolesterase
Uveal Melanoma
Female
Mutation
Eukaryotic Initiation Factor-1
Melanoma
Phosphoproteins
Prognosis
Aged
Aged, 80 and over
Adult
Retrospective Studies
Male
Middle Aged
Machine learning methods in automated detection of CT enterography findings in Crohn's disease: A feasibility study.
Clinical imaging
Jul 1, 2024
PURPOSE: Qualitative findings in Crohn's disease (CD) can be challenging to reliably report and quantify. We evaluated machine learning methodologies to both standardize the detection of common qualitative findings of ileal CD and determine finding s...
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