BACKGROUND: Identifying high risk factors and predicting lung cancer incidence risk are essential to prevention and intervention of lung cancer for the elderly. We aim to develop lung cancer incidence risk prediction model in the elderly to facilitat...
Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke. Thus, the aim of the study was to identify biomarkers to discriminate stroke patients from healthy individuals based on EEG-MS and clinical features...
Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Rece...
The discovery of circulating fetal and tumor cell-free DNA (cfDNA) molecules in plasma has opened up tremendous opportunities in noninvasive diagnostics such as the detection of fetal chromosomal aneuploidies and cancers and in posttransplantation mo...
BACKGROUND: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic morta...
Hepatorenal syndrome (HRS) is a key contributor to poor prognosis in liver cirrhosis. This study aims to leverage the database to build a predictive model for early identification of high-risk patients. From two sizable public databases, we retrieved...
Biomedical physics & engineering express
Jan 22, 2025
. This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment.. Anatomic distances wer...
OBJECTIVE: This study aimed to establish an optimal model based on machine learning (ML) to predict Valproic acid (VPA) trough concentrations in Chinese adult epilepsy patients.
INTRODUCTION: Activation of the inflammatory response system is involved in the pathogenesis of generalized anxiety disorder (GAD). The purpose of this study was to identify and characterize inflammatory biomarkers in the diagnosis of GAD based on ma...
As education increasingly relies on data-driven methodologies, accurately predicting student performance is essential for implementing timely and effective interventions. The California Student Performance Dataset offers a distinctive basis for analy...
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