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Integrating machine learning with bioinformatics for predicting idiopathic pulmonary fibrosis prognosis: developing an individualized clinical prediction tool.
Exp Biol Med (Maywood)
December 2024
Department of Pediatric Surgery, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic models to personalize treatment strategies for IPF patients.
View Article and Find Full Text PDFTrustworthiness of a machine learning early warning model in medical and surgical inpatients.
JAMIA Open
February 2025
Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, United States.
Objectives: In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.
Materials And Methods: We assessed the scores of an EWS integrated into the electronic health record and calculated every 15 minutes to predict a composite adverse event (AE): all-cause mortality, transfer to intensive care, cardiac arrest, or rapid response team evaluation.
Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning.
Front Immunol
December 2024
Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Background: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their simultaneous occurrence are unclear.
View Article and Find Full Text PDFVASARI 2.0: a new updated MRI VASARI lexicon to predict grading and status in brain glioma.
Front Oncol
December 2024
NeuroRadiology Unit, Ospedale del Mare, Azienda Sanitaria Locale Napoli 1 Centro (ASL NA1 Centro), Naples, Italy.
Introduction: Precision medicine refers to managing brain tumors according to each patient's unique characteristics when it was realized that patients with the same type of tumor differ greatly in terms of survival, responsiveness to treatment, and toxicity of medication. Precision diagnostics can now be advanced through the establishment of imaging biomarkers, which necessitates quantitative image acquisition and processing. The VASARI (Visually AcceSAble Rembrandt Images) manual annotation methodology is an ideal and suitable way to determine the accurate association between genotype and imaging phenotype.
View Article and Find Full Text PDFBackground: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.
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