Results 61 to 70 of about 240,436 (283)

A Development and Validation of an AI Model for Cardiomegaly Detection in Chest X-rays

open access: yesApplied Sciences
In this study, the development of a deep learning approach for distinguishing cardiomegaly in chest X-ray images and its validation process are presented. Typically, radiologists diagnose cardiomegaly by examining X-ray images.
Kang-Hee Lee   +4 more
doaj   +1 more source

Professional satisfaction of radiologists in Switzerland

open access: yesSwiss Medical Weekly, 2011
QUESTIONS UNDER STUDY:To gain insight into the determinants of radiologists’ professional satisfaction in Switzerland. METHODS:Data from 254 members of the Swiss Society of Radiology (76% men) obtained in a questionnaire survey were ...
Huch Kubik
doaj   +1 more source

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization

open access: yes, 2017
We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of parameter optimization using Bayesian optimization (Tree Parzen Estimator,
Kojima, Ryosuke   +6 more
core   +2 more sources

A radiologist’s perspective [PDF]

open access: yesCJEM, 1999
Focused abdominal sonography in trauma (FAST) has in many centres replaced the diagnostic peritoneal lavage (DPL) for the early assessment of acute blunt abdominal trauma. In many cases a negative FAST obviates the need for further imaging and intervention.
openaire   +2 more sources

Changes in Body Composition in Children and Young People Undergoing Treatment for Acute Lymphoblastic Leukemia: A Systematic Review and Meta‐Analysis

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed   +5 more
wiley   +1 more source

Saudi Radiology Personnel’s Perceptions of Artificial Intelligence Implementation: A Cross-Sectional Study

open access: yesJournal of Multidisciplinary Healthcare, 2021
Abdulaziz A Qurashi,1 Rashed K Alanazi,1 Yasser M Alhazmi,1 Ahmed S Almohammadi,1 Walaa M Alsharif,1 Khalid M Alshamrani2,3 1Diagnostic Radiology Technology Department, College of Applied Medical Sciences, Taibah University, Madinah, Saudi Arabia ...
Qurashi AA   +5 more
doaj  

Knowledge and practices of cardiopulmonary arrest and anaphylactic reactions in the radiology department

open access: yesSouth African Journal of Radiology, 2020
Background: Emergencies in the radiology department may arise in critically ill patients who are brought to the department for imaging, interventional procedures or as a result of adverse reactions to contrast media used for imaging. Adverse reactions to
Sarah K. Osiemo   +2 more
doaj   +1 more source

Using digital watermarking to enhance security in wireless medical image transmission [PDF]

open access: yes, 2010
This is the published version of the article. Copyright 2010 Mary Ann Liebert Inc.During the last few years, wireless networks have been increasingly used both inside hospitals and in patients’ homes to transmit medical information.
Aggeliki Giakoumaki   +10 more
core   +1 more source

Parent‐to‐Child Information Disclosure in Pediatric Oncology

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor   +12 more
wiley   +1 more source

SAGE: Sequential Attribute Generator for Analyzing Glioblastomas using Limited Dataset

open access: yes, 2020
While deep learning approaches have shown remarkable performance in many imaging tasks, most of these methods rely on availability of large quantities of data. Medical image data, however, is scarce and fragmented.
Allen, Jason   +5 more
core  

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