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Machine learning techniques for independent gait recovery prediction in acute anterior circulation ischemic stroke.
Journal of neuroengineering and rehabilitation
Feb 1, 2025
OBJECTIVE: This study aimed to develop and validate a machine learning-based predictive model for gait recovery in patients with acute anterior circulation ischemic stroke.
Deep learning for automated hip fracture detection and classification : achieving superior accuracy.
The bone & joint journal
Feb 1, 2025
AIMS: The aim of this study was to develop and evaluate a deep learning-based model for classification of hip fractures to enhance diagnostic accuracy.
Development and validation of an interpretable machine learning model to predict major adverse cardiovascular events after noncardiac surgery in geriatric patients: a prospective study.
International journal of surgery (London, England)
Feb 1, 2025
BACKGROUND: Major adverse cardiovascular events (MACEs) within 30 days following noncardiac surgery are prognostically relevant. Accurate prediction of risk and modifiable risk factors for postoperative MACEs is critical for surgical planning and pat...
Predicting early recurrence in locally advanced gastric cancer after gastrectomy using CT-based deep learning model: a multicenter study.
International journal of surgery (London, England)
Feb 1, 2025
BACKGROUND: Early recurrence in patients with locally advanced gastric cancer (LAGC) portends aggressive biological characteristics and a dismal prognosis. Predicting early recurrence may help determine treatment strategies for LAGC. The goal is to d...
Machine learning-based risk prediction of mild cognitive impairment in patients with chronic heart failure: A model development and validation study.
Geriatric nursing (New York, N.Y.)
Feb 1, 2025
Accurate identification of individuals at high risk for mild cognitive impairment (MCI) among chronic heart failure (CHF) patients is crucial for reducing rehospitalization and mortality rates. This study aimed to develop and validate a machine learn...
Automated measurement of pelvic parameters using convolutional neural network in complex spinal deformities: overcoming challenges in coronal deformity cases.
The spine journal : official journal of the North American Spine Society
Jan 31, 2025
BACKGROUND CONTEXT: Accurate and consistent measurement of sagittal alignment is challenging, particularly in patients with severe coronal deformities, including degenerative lumbar scoliosis (DLS).
Statin use and longitudinal bone marrow lesion burden: analysis of knees without osteoarthritis from the Osteoarthritis Initiative study.
Skeletal radiology
Jan 31, 2025
OBJECTIVES: Knee subchondral bone marrow lesions (BMLs) are one of the hallmark features of structural osteoarthritis (OA) and are potential targets for statins' disease-modifying effect. We aimed to determine the association between statin use and l...
Development of a machine learning model and a web application for predicting neurological outcome at hospital discharge in spinal cord injury patients.
The spine journal : official journal of the North American Spine Society
Jan 31, 2025
BACKGROUND: Spinal cord injury (SCI) is a devastating condition with profound physical, psychological, and socioeconomic consequences. Despite advances in SCI treatment, accurately predicting functional recovery remains a significant challenge. Conve...
External validation of 12 existing survival prediction models for patients with spinal metastases.
The spine journal : official journal of the North American Spine Society
Jan 31, 2025
BACKGROUND CONTEXT: Survival prediction models for patients with spinal metastases may inform patients and clinicians in shared decision-making.
Smart home-assisted anomaly detection system for older adults: a deep learning approach with a comprehensive set of daily activities.
Medical & biological engineering & computing
Jan 31, 2025
Smart homes have the potential to enable remote monitoring of the health and well-being of older adults, leading to improved health outcomes and increased independence. However, current approaches only consider a limited set of daily activities and d...
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