AIMC Topic: Cohort Studies
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1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction.
Medicina (Kaunas, Lithuania)
Mar 29, 2024
: Patients presenting with ST Elevation Myocardial Infarction (STEMI) due to occlusive coronary arteries remain at a higher risk of excess morbidity and mortality despite being treated with primary percutaneous coronary intervention (PPCI). Identifyi...
Prediction of metabolic syndrome following a first pregnancy.
American journal of obstetrics and gynecology
Mar 26, 2024
BACKGROUND: The prevalence of metabolic syndrome is rapidly increasing in the United States. We hypothesized that prediction models using data obtained during pregnancy can accurately predict the future development of metabolic syndrome.
Identification of pancreatic cancer risk factors from clinical notes using natural language processing.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Mar 26, 2024
OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of ris...
Transcranial Magnetic Stimulation-Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas.
Neurosurgery
Mar 21, 2024
BACKGROUND: Navigated transcranial magnetic stimulation (nTMS) is a well-established preoperative mapping tool for motor-eloquent glioma surgery. Machine learning (ML) and nTMS may improve clinical outcome prediction and histological correlation.
Predicting the Severity and Discharge Prognosis of Traumatic Brain Injury Based on Intracranial Pressure Data Using Machine Learning Algorithms.
World neurosurgery
Mar 20, 2024
OBJECTIVE: This study aimed to explore the potential of employing machine learning algorithms based on intracranial pressure (ICP), ICP-derived parameters, and their complexity to predict the severity and short-term prognosis of traumatic brain injur...
Enhancing the prediction of symptomatic radiation pneumonitis for locally advanced non-small-cell lung cancer by combining 3D deep learning-derived imaging features with dose-volume metrics: a two-center study.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Mar 18, 2024
OBJECTIVE: This study aims to examine the ability of deep learning (DL)-derived imaging features for the prediction of radiation pneumonitis (RP) in locally advanced non-small-cell lung cancer (LA-NSCLC) patients.
Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.
BMJ open
Mar 14, 2024
OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.
Prognostic factors among patients with pathological Grade Group 5 prostate cancer based on robot-associated radical prostatectomy specimens from a large Japanese cohort (MSUG94).
World journal of urology
Mar 14, 2024
PURPOSE: There are no definitive prognostic factors for patients with pathological Grade Group 5 (pGG 5) prostate cancer (PCa) undergoing robot-associated radical prostatectomy (RARP). This study aimed to explore the prognostic factors among patients...
Effects of thienopyridine class antiplatelets on bleeding outcomes following robot-assisted radical prostatectomy.
Scientific reports
Mar 11, 2024
This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlopidine, clopidogrel, and prasugrel) on bleeding complications in patients who underwent robot-assisted radical prostatectomy. This cohort study used a ...
Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort.
Medical & biological engineering & computing
Mar 7, 2024
Revision total knee arthroplasty (TKA) is associated with a higher risk of readmission than primary TKA. Identifying individual patients predisposed to readmission can facilitate proactive optimization and increase care efficiency. This study develop...
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