Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/s0022-5347(17)61975-x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A deep learning based model for diabetic retinopathy grading.
Sci Rep
January 2025
Department of Networks and Cybersecurity, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Existing methods to detect this disease often rely on handcrafted features which limit the adaptability and classification accuracy.
View Article and Find Full Text PDFAre Non-invasive Multi-cancer Early Cancer Detection Tests the Future?
Dig Dis Sci
January 2025
Gastroenterology, University of Washington School of Medicine, Seattle, USA.
Current cancer screening methods are effective for detecting early stage cancers and even preventing some cancers, but their effectiveness has only been demonstrated for a handful of cancers, and for many cancers, there are no screening tests clinically available. In addition, the majority of the screening methods are not ideal, resulting in suboptimal compliance and the occurrence of preventable cancers. A screening test that is convenient, safe, accurate and that can screen for multiple cancers is an ideal screening test that would address many of the shortcomings of the current tests.
View Article and Find Full Text PDFPositive Lymph Node Status Before and After Neoadjuvant Chemoradiotherapy Improves Prediction of Disease-Free Survival in Esophageal Squamous Cell Carcinoma Patients.
Ann Surg Oncol
January 2025
Departments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Background: This study proposes a modified lymph node (LN) staging category (BALN) on the basis of the number of positive LNs before (prepN) and after (ypN) neoadjuvant chemoradiotherapy (nCRT) to improve prognostic stratification in esophageal squamous cell carcinoma (ESCC).
Patients And Methods: A total of 381 patients with ESCC who underwent nCRT at three medical centers were retrospectively enrolled. The ypN categories were scored according to the eighth edition of the American Joint Committee of Cancer (AJCC) staging manual.
Predicting and managing liver fibrosis in biliary atresia.
Semin Pediatr Surg
January 2025
Section of Pediatric Surgery, Pediatric Liver and Gut Research Group, New Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Pediatric Research Center, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden. Electronic address:
Regardless of the underlying etiology and success of PE, progressive liver fibrosis and eventually cirrhosis represent the dominant pathology and the end-stage of BA. Ascending bile duct injury-induced cholestasis, inflammation and ductular reaction provide profibrogenic cytokine environment leading to myofibroblast activation and rapid progression of fibrosis especially after unsuccessful portoenterostomy. Although liver fibrosis and development of cirrhosis play a crucial role in determining BA outcomes, the exact prognostic significance and dynamics of mild to moderate liver fibrosis remain unclear.
View Article and Find Full Text PDFUnveiling the Content of Frontal Feedback in Challenging Object Recognition.
Neuroimage
January 2025
School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran, Iran. Electronic address:
Object recognition under challenging real-world conditions, including partial occlusion, remains an enduring focus of investigation in cognitive visual neuroscience. This study addresses the insufficiently elucidated neural mechanisms and temporal dynamics involved in this complex process, concentrating on the persistent challenge of recognizing objects obscured by occlusion. Through the analysis of human EEG data, we decode feedback characteristics within frontotemporal networks, uncovering intricate neural mechanisms during occlusion coding, with a specific emphasis on processing complex stimuli such as occluded faces.
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!