The subject of this Research Issues Column is privacy as it applies to healthcare. To that end, the notion of privacy from the perspective of the law is considered, followed by a consideration of its linkage to healthcare. This serves as an introduction to research on opinions of physicians and nurses in Turkey about the nature of privacy for the patients they serve.
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| http://dx.doi.org/10.1177/0894318420987172 | DOI Listing |
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Evaluation of an enhanced ResNet-18 classification model for rapid On-site diagnosis in respiratory cytology.
BMC Cancer
January 2025
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Objective: Rapid on-site evaluation (ROSE) of respiratory cytology specimens is a critical technique for accurate and timely diagnosis of lung cancer. However, in China, limited familiarity with the Diff-Quik staining method and a shortage of trained cytopathologists hamper utilization of ROSE. Therefore, developing an improved deep learning model to assist clinicians in promptly and accurately evaluating Diff-Quik stained cytology samples during ROSE has important clinical value.
View Article and Find Full Text PDFNavigating technostress: a deep dive into health practitioners' technological challenges in hospital settings.
BMC Health Serv Res
January 2025
School of Library and Information Management, Emporia State University, Emporia, KS, USA.
Background And Purpose: Despite the increasing integration of information technologies in healthcare settings, limited attention has been given to understanding technostress among health practitioners in hospitals. This study aims to assess the prevalence of technostress creators among health practitioners and explore potential factors contributing to its occurrence, with the ultimate goal of informing strategies to mitigate its impact.
Method: Data were collected through a validated questionnaire administered to health practitioners at Tehran Apadana Hospital in Iran.
Predictors and prognosis of elderly hip fracture patients with perioperative atrial fibrillation: a nested case-control study.
BMC Geriatr
January 2025
Department of Orthopaedic Surgery, The Third Hospital of Hebei Medical University, No.139, ZiQiang Lu, Shijiazhuang, Hebei, 050051, PR China.
Background: A scarcity of data exists concerning atrial fibrillation (AF) during the perioperative stage of non-cardiothoracic surgery, particularly orthopedic surgery. In addition, given the frequency and significant impact of AF in the perioperative period, therefore our aim was to identify prognosis and predictors of elderly hip fracture patients with perioperative AF.
Methods: An examination of hip fracture patients at the Third Hospital of Hebei Medical University, who had been hospitalized from January 2018 to October 2020 in succession, was conducted retrospectively.
Generating unseen diseases patient data using ontology enhanced generative adversarial networks.
NPJ Digit Med
January 2025
Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, the Netherlands.
Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards.
View Article and Find Full Text PDFA Faster Privacy-Preserving Medical Image Diagnosis Scheme with Machine Learning.
J Imaging Inform Med
January 2025
College of Computer, Chongqing University, No. 55 Daxuecheng South Rd, Shapingba, 401331, Chongqing, China.
Convolutional neural networks (CNNs) have become indispensable to medical image diagnosis research, enabling the automated differentiation of diseased images from extensive medical image datasets. Due to their efficacy, these methods raise significant privacy concerns regarding patient images and diagnostic models. To address these issues, some researchers have explored privacy-preserving medical image diagnosis schemes using fully homomorphic encryption (FHE).
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