Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jjo.2003.08.005 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Biologically-targeted discovery-replication scan identifies G×G interaction in relation to risk of Barrett's esophagus and esophageal adenocarcinoma.
HGG Adv
January 2025
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196).
View Article and Find Full Text PDFGenetic landscape in undiagnosed patients with syndromic hearing loss revealed by whole exome sequencing and phenotype similarity search.
Hum Genet
January 2025
Division of Hearing and Balance Research, National Institute of Sensory Organs, NHO Tokyo Medical Center, 2-5-1 Higashigaoka, Meguro-Ku, Tokyo, 152-8902, Japan.
There are hundreds of rare syndromic diseases involving hearing loss, many of which are not targeted for clinical genetic testing. We systematically explored the genetic causes of undiagnosed syndromic hearing loss using a combination of whole exome sequencing (WES) and a phenotype similarity search system called PubCaseFinder. Fifty-five families with syndromic hearing loss of unknown cause were analyzed using WES after prescreening of several deafness genes depending on patient clinical features.
View Article and Find Full Text PDFEnhancing security and efficiency in Mobile Ad Hoc Networks using a hybrid deep learning model for flooding attack detection.
Sci Rep
January 2025
North Carolina School of Science and Mathematics, Durham, NC, 27705, USA.
Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.
View Article and Find Full Text PDFFeasibility study of hyperspectral colposcopy as a novel tool for detecting precancerous cervical lesions.
Sci Rep
January 2025
Research Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), Las Palmas de Gran Canaria, Spain.
Cervical cancer remains a major global health concern, with a specially alarming incidence in younger women. Traditional detection techniques such as the Pap smear and colposcopy often lack sensitivity and specificity and are highly dependent on the experience of the gynaecologist. In response, this study proposes the use of Hyperspectral Imaging, a pioneering technology that combines traditional imaging with spectroscopy to provide detailed spatial and spectral information.
View Article and Find Full Text PDFPointer meters recognition method in the wild based on innovative deep learning techniques.
Sci Rep
January 2025
College of Computer and Data Science, Minjiang University, Fuzhou, 350018, China.
This study presents a novel approach to identifying meters and their pointers in modern industrial scenarios using deep learning. We developed a neural network model that can detect gauges and one or more of their pointers on low-quality images. We use an encoder network, jump connections, and a modified Convolutional Block Attention Module (CBAM) to detect gauge panels and pointer keypoints in images.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!