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Combined embedding model for MiRNA-disease association prediction.

BMC bioinformatics
BACKGROUND: Cumulative evidence from biological experiments has confirmed that miRNAs have significant roles to diagnose and treat complex diseases. However, traditional medical experiments have limitations in time-consuming and high cost so that the...

Development and performance of CUHAS-ROBUST application for pulmonary rifampicin-resistance tuberculosis screening in Indonesia.

PloS one
BACKGROUND AND OBJECTIVES: Diagnosis of Pulmonary Rifampicin Resistant Tuberculosis (RR-TB) with the Drug-Susceptibility Test (DST) is costly and time-consuming. Furthermore, GeneXpert for rapid diagnosis is not widely available in Indonesia. This st...

Artificial neural networks versus LASSO regression for the prediction of long-term survival after surgery for invasive IPMN of the pancreas.

PloS one
Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (IPMN) of the pancreas may aid in patient assessment, risk stratification and personalization of treatment. This study aimed to investigate the predict...

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning.

PloS one
BACKGROUND: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of sympto...

Sustained results of robotic mitral repair in a lower volume center with extensive minimally invasive mitral repair experience.

Journal of robotic surgery
The literature for robotic mitral repair is dominated by a small number of large volume institutions, and intermediate-term outcomes out to 5 years are rare. Whether and under what circumstances a lower volume institution could obtain durable outcome...

Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.

The Lancet. Digital health
BACKGROUND: Chest x-ray is a relatively accessible, inexpensive, fast imaging modality that might be valuable in the prognostication of patients with COVID-19. We aimed to develop and evaluate an artificial intelligence system using chest x-rays and ...

In vivo evaluation of angulated needle-guide template for MRI-guided transperineal prostate biopsy.

Medical physics
PURPOSE: Magnetic resonance imaging (MRI)-guided transperineal prostate biopsy has been practiced since the early 2000s. The technique often suffers from targeting error due to deviation of the needle as a result of physical interaction between the n...

A machine learning-based survival prediction model of high grade glioma by integration of clinical and dose-volume histogram parameters.

Cancer medicine
PURPOSE: Glioma is the most common type of primary brain tumor in adults, and it causes significant morbidity and mortality, especially in high-grade glioma (HGG) patients. The accurate prognostic prediction of HGG is vital and helpful for clinicians...

Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BMC pulmonary medicine
BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and interpretations vary widely between users. The digitization of auscultation acquisition and interpretati...

Improved detection of air trapping on expiratory computed tomography using deep learning.

PloS one
BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are...