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A commercial AI tool untrained for COVID-19 demonstrates slight improvement in the interpretation of COVID-19 pneumonia x-rays, especially among inexperienced readers.
Radiologia
Jan 24, 2025
INTRODUCTION: Our objective is to evaluate how useful an artificial intelligence (AI) tool is to chest radiograph readers with various levels of expertise for the diagnosis of COVID-19 pneumonia when the tool has been trained on a non-COVID-19 pneumo...
Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.
JCO clinical cancer informatics
Jan 24, 2025
PURPOSE: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evalu...
AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.
PloS one
Jan 24, 2025
To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings for rib fractures (RFs) detection on CT images. This study included 243 consecutive chest trauma pat...
Machine learning model to predict the adherence of tuberculosis patients experiencing increased levels of liver enzymes in Indonesia.
PloS one
Jan 24, 2025
Indonesia is still the second-highest tuberculosis burden country in the world. The antituberculosis adverse drug reaction and adherence may influence the success of treatment. The objective of this study is to define the model for predicting the adh...
Explainable machine learning model for assessing health status in patients with comorbid coronary heart disease and depression: Development and validation study.
International journal of medical informatics
Jan 23, 2025
BACKGROUND: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and vali...
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...
Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems.
Circulation. Genomic and precision medicine
Jan 23, 2025
BACKGROUND: While universal screening for Lipoprotein(a) [Lp(a)] is increasingly recommended, <0.5% of patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a) (ARISE), a ...
Random Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.
Circulation. Genomic and precision medicine
Jan 23, 2025
BACKGROUND: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease.
Clinical validation of an individualized auto-adaptative serious game for combined cognitive and upper limb motor robotic rehabilitation after stroke.
Journal of neuroengineering and rehabilitation
Jan 23, 2025
BACKGROUND: Intensive rehabilitation through challenging and individualized tasks are recommended to enhance upper limb recovery after stroke. Robot-assisted therapy (RAT) and serious games could be used to enhance functional recovery by providing si...
Development and validation of a novel artificial intelligence algorithm for precise prediction the postoperative prognosis of esophageal squamous cell carcinoma.
BMC cancer
Jan 23, 2025
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy, and current postoperative prognostic assessment methods remain unsatisfactory, underlining the urgent to develop a reliable approach for precision medicine. Give...
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