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Fair prediction of 2-year stroke risk in patients with atrial fibrillation.
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2024
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.
Evaluation of a Deep Learning Model for Metastatic Squamous Cell Carcinoma Prediction From Whole Slide Images.
Archives of pathology & laboratory medicine
Dec 1, 2024
CONTEXT.—: Squamous cell carcinoma (SCC) is a histologic type of cancer that exhibits various degrees of keratinization. Identifying lymph node metastasis in SCC is crucial for prognosis and treatment strategies. Although artificial intelligence (AI)...
[Investigation of the impact of the deep learning based CT fractional flow reserve on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease].
Zhonghua xin xue guan bing za zhi
Nov 24, 2024
To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease. In this single-center retrospective cohort study, cons...
Identification and validation of oxidative stress-related genes in primary open-angle glaucoma by weighted gene co-expression network analysis and machine learning.
Medicine
Nov 15, 2024
Primary open-angle glaucoma (POAG) is a common ocular disease, and there is currently no effective treatment for POAG therapy. Thus, identifying some effective diagnostic markers is beneficial to the treatment of patients. The expression profile was ...
Integrated machine learning developed a prognosis-related gene signature to predict prognosis in oesophageal squamous cell carcinoma.
Journal of cellular and molecular medicine
Nov 1, 2024
The mortality rate of oesophageal squamous cell carcinoma (ESCC) remains high, and conventional TNM systems cannot accurately predict its prognosis, thus necessitating a predictive model. In this study, a 17-gene prognosis-related gene signature (PRS...
Development and Validation of Machine Learning Models for Identifying Prediabetes and Diabetes in Normoglycemia.
Diabetes/metabolism research and reviews
Nov 1, 2024
BACKGROUND: Prediabetes and diabetes are both abnormal states of glucose metabolism (AGM) that can lead to severe complications. Early detection of AGM is crucial for timely intervention and treatment. However, fasting blood glucose (FBG) as a mass p...
Development of machine learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma.
Medicine
Nov 1, 2024
The aim of this study was to develop a machine-learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma. We included patients who underwent craniotomy and evacuation of hematoma due to traumatic brain inj...
Deep Learning to Discriminate Arteritic From Nonarteritic Ischemic Optic Neuropathy on Color Images.
JAMA ophthalmology
Nov 1, 2024
IMPORTANCE: Prompt and accurate diagnosis of arteritic anterior ischemic optic neuropathy (AAION) from giant cell arteritis and other systemic vasculitis can contribute to preventing irreversible vision loss from these conditions. Its clinical distin...
Addressing the Generalizability of AI in Radiology Using a Novel Data Augmentation Framework with Synthetic Patient Image Data: Proof-of-Concept and External Validation for Classification Tasks in Multiple Sclerosis.
Radiology. Artificial intelligence
Nov 1, 2024
Artificial intelligence (AI) models often face performance drops after deployment to external datasets. This study evaluated the potential of a novel data augmentation framework based on generative adversarial networks (GANs) that creates synthetic p...
Impact of wearable device data and multi-scale entropy analysis on improving hospital readmission prediction.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVE: Unplanned readmissions following a hospitalization remain common despite significant efforts to curtail these. Wearable devices may offer help identify patients at high risk for an unplanned readmission.
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