AIMC Topic: Cohort Studies
Clear Filters Showing 71 to 80 of 1169 articles
Enhancing individual glomerular filtration rate assessment: can we trust the equation? Development and validation of machine learning models to assess the trustworthiness of estimated GFR compared to measured GFR.
BMC nephrology
Jan 30, 2025
BACKGROUND: Creatinine-based estimated glomerular filtration rate (eGFR) equations are widely used in clinical practice but exhibit inherent limitations. On the other side, measuring GFR is time consuming and not available in routine clinical practic...
Machine Learning to Predict Mortality in Older Patients With Cancer: Development and External Validation of the Geriatric Cancer Scoring System Using Two Large French Cohorts.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Jan 24, 2025
PURPOSE: Establishing an accurate prognosis remains challenging in older patients with cancer because of the population's heterogeneity and the current predictive models' reduced ability to capture the complex interactions between oncologic and geria...
Artificial intelligence-enabled obesity prediction: A systematic review of cohort data analysis.
International journal of medical informatics
Jan 24, 2025
BACKGROUND: Obesity, now the fifth leading global cause of death, has seen a dramatic rise in prevalence over the last forty years. It significantly increases the risk of diseases such as type 2 diabetes and cardiovascular disease. Early identificati...
Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.
Respiratory research
Jan 24, 2025
BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapidly evolving interstitial lung disease (ILD), driving its mortality. Specific imaging-based biomarkers associated with the evolution of lung disease are need...
Application of elastic net for clinical outcome prediction and classification in progressive supranuclear palsy: A multicenter cohort study.
Parkinsonism & related disorders
Jan 23, 2025
BACKGROUND: Previous studies have used machine learning to identify clinically relevant atrophic regions in progressive supranuclear palsy (PSP). This study applied Elastic Net (EN) in PSP to uncover key atrophic patterns, offering a novel approach t...
Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study.
JMIR medical informatics
Jan 22, 2025
BACKGROUND: Cohort studies contain rich clinical data across large and diverse patient populations and are a common source of observational data for clinical research. Because large scale cohort studies are both time and resource intensive, one alter...
Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.
Journal of medical Internet research
Jan 22, 2025
BACKGROUND: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic morta...
Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia.
Translational psychiatry
Jan 21, 2025
Existing dementia prediction models using non-neuroimaging clinical measures have been limited in their ability to identify disease. This study used machine learning to re-examine the diagnostic potential of clinical measures for dementia. Data was s...
Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health records.
International journal of medical informatics
Jan 17, 2025
BACKGROUND: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electro...
Evaluating a clinically available artificial intelligence model for intracranial aneurysm detection: a multi-reader study and algorithmic audit.
Neuroradiology
Jan 15, 2025
PURPOSE: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracranial aneurysm (IA) in a multi-reader multi-case (MRMC) study, and to explore its performance in routine...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823