AIMC Topic: Aged, 80 and over
Clear Filters Showing 751 to 760 of 3432 articles
Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.
Journal of applied gerontology : the official journal of the Southern Gerontological Society
Aug 6, 2024
This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...
Artificial intelligence prediction of In-Hospital mortality in patients with dementia: A multi-center study.
International journal of medical informatics
Aug 6, 2024
BACKGROUND: Prediction of mortality is very important for care planning in hospitalized patients with dementia and artificial intelligence has the potential to serve as a solution; however, this issue remains unclear. Thus, this study was conducted t...
Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 6, 2024
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...
Medical Futility
Humans
Male
Middle Aged
Risk Assessment
Time Factors
Clinical Decision-Making
Predictive Value of Tests
Machine Learning
Treatment Outcome
Female
Ischemic Stroke
Decision Support Techniques
Risk Factors
Radiographic Image Interpretation, Computer-Assisted
Retrospective Studies
Aged
Infarction, Middle Cerebral Artery
Tomography, X-Ray Computed
Aged, 80 and over
Thrombectomy
Deep learning reconstruction for optimized bone assessment in zero echo time MR imaging of the knee.
European journal of radiology
Aug 4, 2024
PURPOSE: To evaluate the impact of deep learning-based reconstruction (DLRecon) on bone assessment in zero echo-time (ZTE) MRI of the knee at 1.5 Tesla.
Integrating Deep Learning-Based Dose Distribution Prediction with Bayesian Networks for Decision Support in Radiotherapy for Upper Gastrointestinal Cancer.
Cancer research and treatment
Aug 2, 2024
PURPOSE: Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) or magnetic resonance-guided gated delivery using MRIdian (MRG), is time-consuming and costly. To add...
Botulinum Toxin Type A (BoNT-A) Use for Post-Stroke Spasticity: A Multicenter Study Using Natural Language Processing and Machine Learning.
Toxins
Aug 2, 2024
We conducted a multicenter and retrospective study to describe the use of botulinum toxin type A (BoNT-A) to treat post-stroke spasticity (PSS). Data were extracted from free-text in electronic health records (EHRs) in five Spanish hospitals. We incl...
Machine learning in diagnostic support in medical emergency departments.
Scientific reports
Aug 2, 2024
Diagnosing patients in the medical emergency department is complex and this is expected to increase in many countries due to an ageing population. In this study we investigate the feasibility of training machine learning algorithms to assist physicia...
Deep learning predicts the 1-year prognosis of pancreatic cancer patients using positive peritoneal washing cytology.
Scientific reports
Aug 2, 2024
Peritoneal washing cytology (CY) in patients with pancreatic cancer is mainly used for staging; however, it may also be used to evaluate the intraperitoneal status to predict a more accurate prognosis. Here, we investigated the potential of deep lear...
A machine learning technology for addressing medication-related risk in older, multimorbid patients.
The American journal of managed care
Aug 1, 2024
OBJECTIVES: To evaluate the FeelBetter machine learning system's ability to accurately identify older patients with multimorbidity at Brigham and Women's Hospital at highest risk of medication-associated emergency department (ED) visits and hospitali...
Artificial Intelligence Machine Learning Algorithms Versus Standard Linear Demographic Analysis in Predicting Implant Size of Anatomic and Reverse Total Shoulder Arthroplasty.
Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews
Aug 1, 2024
BACKGROUND: Accurate and precise templating is paramount for anatomic total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty (RSA) to enhance preoperative planning, streamline surgery, and improve implant positioning. We aimed to e...
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