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Detecting anomalies in smart wearables for hypertension: a deep learning mechanism.
Front Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
View Article and Find Full Text PDFIntegrating traditional machine learning with qPCR validation to identify solid drug targets in pancreatic cancer: a 5-gene signature study.
Front Pharmacol
January 2025
Department of General Surgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
Background: Pancreatic cancer remains one of the deadliest malignancies, largely due to its late diagnosis and lack of effective therapeutic targets.
Materials And Methods: Using traditional machine learning methods, including random-effects meta-analysis and forward-search optimization, we developed a robust signature validated across 14 publicly available datasets, achieving a summary AUC of 0.99 in training datasets and 0.
Analysis of fetal fraction in non-invasive prenatal testing with low-depth whole genome sequencing.
Heliyon
January 2025
Molecular Diagnosis Center, Affiliated Qingyuan Hospital, Guangzhou Medical University (Qingyuan People's Hospital), 511518, Qingyuan, China.
Background: The fetal fraction (FF) is a critical factor influencing the performance of non-invasive prenatal testing (NIPT). Different NIPT methods and sequencing depths can lead to distinct minimum FF thresholds for Trisomy 21 (T21). This study aims to analyze the minimum FF thresholds for detecting T21 in PCR-free NIPT using a low-depth whole genome sequencing method.
View Article and Find Full Text PDFPrediction of isocitrate dehydrogenase mutation status in WHO grade II glioma by diffusion kurtosis imaging.
Pol J Radiol
December 2024
First Hospital of Shanxi Medical University, Shanxi, China.
Purpose: Isocitrate dehydrogenase (IDH) mutation status serves as a crucial prognostic indicator for glioma, typically assessed via immunohistochemical analysis post-surgery. Given the invasiveness of this approach, perhaps we can utilise convenient and noninvasive magnetic resonance imaging (MRI) methods to predict IDH mutation status. However, the current landscape lacks a standardised MRI technique for accurately predicting IDH mutations.
View Article and Find Full Text PDFIncidental Diagnosis of Occult Maternal Malignancy With Routine Noninvasive Prenatal Testing During Pregnancy.
Cureus
December 2024
Maternal Fetal Medicine, Michigan State University College of Human Medicine/Corewell Health, Grand Rapids, USA.
The noninvasive prenatal test (NIPT) for genetic screening has been adopted globally as an alternative to first-trimester and quad screening due to its high sensitivity and specificity. NIPT involves detecting and processing foreign fetal DNA in maternal circulation to screen for fetal aneuploidy. An incidental consequence of this process is the detection of foreign tumor cell DNA in maternal circulation in otherwise asymptomatic patients.
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