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Online Unsupervised Adaptation of Latent Representation for Myoelectric Control During User-Decoder Co-Adaptation.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 6, 2025
Myoelectric control interfaces, which map electromyographic (EMG) signals into control commands for external devices, have applications in active prosthesis control. However, the statistical characteristics of EMG signals change over time (e.g., beca...
Evaluating fusion models for predicting occult lymph node metastasis in tongue squamous cell carcinoma.
European radiology
Mar 5, 2025
OBJECTIVES: This study evaluated and compared the effectiveness of various predictive models for forecasting occult lymph node metastasis (LNM) in tongue squamous cell carcinoma (TSCC) patients.
Development of Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer Patients Using Clinical Risk Factors, Patient-Reported Outcomes, and Serum Cytokine Biomarkers.
Clinical breast cancer
Mar 5, 2025
BACKGROUND: Radiation dermatitis (RD) is a significant side effect of radiotherapy experienced by breast cancer patients. Severe symptoms include desquamation or ulceration of irradiated skin, which impacts quality of life and increases healthcare co...
Altered Gut Microbiome Composition and Function in Individuals with Complex Regional Pain Syndrome.
Anesthesiology
Mar 5, 2025
BACKGROUND: Complex regional pain syndrome is a chronic pain syndrome typically affecting a limb. It is characterized by severe spontaneous and evoked pain, along with vasomotor, autonomic, and motor signs and symptoms. Although dysregulation in seve...
Dual-type deep learning-based image reconstruction for advanced denoising and super-resolution processing in head and neck T2-weighted imaging.
Japanese journal of radiology
Mar 5, 2025
PURPOSE: To assess the utility of dual-type deep learning (DL)-based image reconstruction with DL-based image denoising and super-resolution processing by comparing images reconstructed with the conventional method in head and neck fat-suppressed (Fs...
Added value of artificial intelligence for the detection of pelvic and hip fractures.
Japanese journal of radiology
Mar 5, 2025
PURPOSE: To assess the added value of artificial intelligence (AI) for radiologists and emergency physicians in the radiographic detection of pelvic fractures.
Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.
Computers in biology and medicine
Mar 5, 2025
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
Risk Assessment
Case-Control Studies
Adolescent
Suicide Prevention
United States
Young Adult
Humans
Adult
Natural Language Processing
Suicide, Completed
Electronic Health Records
Male
Female
Predictive Learning Models
United States Department of Veterans Affairs
Aged
Psychological Well-Being
Middle Aged
Veterans
Aged, 80 and over
United States Department of Defense
Development of Hybrid radiomic Machine learning models for preoperative prediction of meningioma grade on multiparametric MRI.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mar 5, 2025
PURPOSE: To develop and compare machine learning models for distinguishing low and high grade meningiomas on multiparametric MRI.
Determining the Importance of Lifestyle Risk Factors in Predicting Binge Eating Disorder After Bariatric Surgery Using Machine Learning Models and Lifestyle Scores.
Obesity surgery
Mar 5, 2025
BACKGROUND: This study was conducted to assess the association between lifestyle risk factors (LRF) and odds of binge eating disorder (BED) 2 years post laparoscopic sleeve gastrectomy (LSG) using lifestyle score (LS) and machine learning (ML) models...
A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.
Psychiatric genetics
Mar 5, 2025
BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and treatment efficacy is variable across patients. Polymorphisms in cytochrome P450 2C19 (CYP2C19) play a role in response and side effects to medication...
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