AIMC Topic: Retrospective Studies
Clear Filters Showing 551 to 560 of 9163 articles
Natural language processing of electronic medical records identifies cardioprotective agents for anthracycline induced cardiotoxicity.
Scientific reports
Feb 24, 2025
In this retrospective observational study, we aimed to investigate the potential of natural language processing (NLP) for drug repositioning by analyzing the preventive effects of cardioprotective drugs against anthracycline-induced cardiotoxicity (A...
Natural Language Processing
Humans
Calcium Channel Blockers
Retrospective Studies
Hydroxymethylglutaryl-CoA Reductase Inhibitors
Electronic Health Records
Angiotensin Receptor Antagonists
Female
Angiotensin-Converting Enzyme Inhibitors
Aged
Adult
Male
Middle Aged
Cardiotonic Agents
Drug Repositioning
Cardiotoxicity
Anthracyclines
Adrenergic beta-Antagonists
Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.
Acta neurochirurgica
Feb 24, 2025
PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitating the prediction of treatment outcomes and patient survival. However, the effectiveness of ML models heavily relies on both the choice of algorithms...
Multimodal Artificial Intelligence-Based Virtual Biopsy for Diagnosing Abdominal Lavage Cytology-Positive Gastric Cancer.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 22, 2025
Gastric cancer with peritoneal dissemination remains a significant clinical challenge due to its poor prognosis and difficulty in early detection. This study introduces a multimodal artificial intelligence-based risk stratification assessment (RSA) m...
Machine learning based on nutritional assessment to predict adverse events in older inpatients with possible sarcopenia.
Aging clinical and experimental research
Feb 22, 2025
BACKGROUND: The accuracy of current tools for predicting adverse events in older inpatients with possible sarcopenia is still insufficient to develop individualized nutrition-related management strategies. The objectives were to develop a machine lea...
Artificial intelligence assessment of tissue-dissection efficiency in laparoscopic colorectal surgery.
Langenbeck's archives of surgery
Feb 22, 2025
PURPOSE: Several surgical-skill assessment tools emphasize the importance of efficient tissue-dissection, whose assessment relies on human judgment and is thus subject to bias. Automated assessment may help solve this problem. This study aimed to ver...
Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Feb 21, 2025
BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses mac...
Male
Middle Aged
Severity of Illness Index
Treatment Outcome
Predictive Value of Tests
Retrospective Studies
Female
Reproducibility of Results
Aged
Stents
Image Interpretation, Computer-Assisted
Ultrasonography, Interventional
Humans
Observer Variation
Percutaneous Coronary Intervention
Machine Learning
Automation
Coronary Artery Disease
Coronary Vessels
Prosthesis Design
Utilizing 12-lead electrocardiogram and machine learning to retrospectively estimate and prospectively predict atrial fibrillation and stroke risk.
Computers in biology and medicine
Feb 21, 2025
BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated. By identifying patients at high risk of embolic stroke, health-care professionals can make more informed decisions regarding anticoagulation treatmen...
A knowledge-based planning model to identify fraction-reduction opportunities in brain stereotactic radiotherapy.
Journal of applied clinical medical physics
Feb 21, 2025
OBJECTIVE: To develop and validate a HyperArc-based RapidPlan (HARP) model for three-fraction brain stereotactic radiotherapy (SRT) plans to then use to replan previously treated five-fraction SRT plans. Demonstrating the possibility of reducing the ...
An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation.
Medicina (Kaunas, Lithuania)
Feb 21, 2025
: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic stenosis are critical for patient prognosis. Accurate prediction of adverse events can enhance patient management and improve outcomes. : This study ai...
Development and external validation of a machine learning-based model to predict postoperative recurrence in patients with duodenal adenocarcinoma: a multicenter, retrospective cohort study.
BMC medicine
Feb 21, 2025
BACKGROUND: Duodenal adenocarcinoma (DA) has a high recurrence rate, making the prediction of recurrence after surgery critically important.
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