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Prediction of 30-day mortality for ICU patients with Sepsis-3.
BMC medical informatics and decision making
Aug 8, 2024
BACKGROUND: There is a growing demand for advanced methods to improve the understanding and prediction of illnesses. This study focuses on Sepsis, a critical response to infection, aiming to enhance early detection and mortality prediction for Sepsis...
A risk prediction model based on machine learning algorithm for parastomal hernia after permanent colostomy.
BMC medical informatics and decision making
Aug 8, 2024
OBJECTIVE: To develop a machine learning-based risk prediction model for postoperative parastomal hernia (PSH) in colorectal cancer patients undergoing permanent colostomy, assisting nurses in identifying high-risk groups and devising preventive care...
Deep learning-based multimodal fusion of the surface ECG and clinical features in prediction of atrial fibrillation recurrence following catheter ablation.
BMC medical informatics and decision making
Aug 8, 2024
BACKGROUND: Despite improvement in treatment strategies for atrial fibrillation (AF), a significant proportion of patients still experience recurrence after ablation. This study aims to propose a novel algorithm based on Transformer using surface ele...
Unbiased identification of risk factors for invasive Escherichia coli disease using machine learning.
BMC infectious diseases
Aug 8, 2024
BACKGROUND: Invasive Escherichia coli disease (IED), also known as invasive extraintestinal pathogenic E. coli disease, is a leading cause of sepsis and bacteremia in older adults that can result in hospitalization and sometimes death and is frequent...
Deep learning-based automated angle measurement for flatfoot diagnosis in weight-bearing lateral radiographs.
Scientific reports
Aug 8, 2024
This study aimed to develop and evaluate a deep learning-based system for the automatic measurement of angles (specifically, Meary's angle and calcaneal pitch) in weight-bearing lateral radiographs of the foot for flatfoot diagnosis. We utilized 3960...
A Cascaded Mutliresolution Ensemble Deep Learning Framework for Large Scale Alzheimer's Disease Detection Using Brain MRIs.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Alzheimer's is progressive and irreversible type of dementia, which causes degeneration and death of cells and their connections in the brain. AD worsens over time and greatly impacts patients' life and affects their important mental functions, inclu...
Diabetic retinopathy screening with confocal fundus camera and artificial intelligence - assisted grading.
European journal of ophthalmology
Aug 7, 2024
PURPOSE: Screening for diabetic retinopathy (DR) by ophthalmologists is costly and labour-intensive. Artificial Intelligence (AI) for automated DR detection could be a clinically and economically alternative. We assessed the performance of a confocal...
Automated remote sleep monitoring needs uncertainty quantification.
Journal of sleep research
Aug 7, 2024
Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage c...
Assessing the use of the novel tool Claude 3 in comparison to ChatGPT 4.0 as an artificial intelligence tool in the diagnosis and therapy of primary head and neck cancer cases.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Aug 7, 2024
Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplinary tumor board approach for individual treatment planning. In recent years, artificial intelligence tools have emerged to assist healthcare professio...
Machine Learning-Based Algorithm for the Early Prediction of Postoperative Hypocalcemia Risk After Thyroidectomy.
Annals of surgery
Aug 7, 2024
OBJECTIVE: We used machine learning to develop and validate a multivariable algorithm allowing the accurate and early prediction of postoperative hypocalcemia risk.
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