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A substantial amount of research has been published on the association between the use of electronic medical records (EMRs) and quality outcomes in U.S. hospitals, while limited research has focused on the Western European experience. The purpose of this study is to explore the association between the use of EMR technologies in Dutch hospitals and length of stay after colorectal cancer surgery. Two data sets were leveraged for this study; the HIMSS Analytics Electronic Medical Record Adoption Model (EMRAM) and the Dutch surgical colorectal audit (DSCA). The HIMSS Analytics EMRAM score was used to define a Dutch hospital's electronic medical records (EMR) capabilities while the DSCA was used to profile colorectal surgery quality outcomes (specifically total length of stay (LOS) in the hospital and the LOS in ICU). A total of 73 hospitals with a valid EMRAM score and associated DSCA patients (n = 30.358) during the study period (2012-2014) were included in the comparative set. A multivariate regression method was used to test differences adjusted for case mix, year of surgery, surgical technique and for complications, as well as stratifying for academic affiliated hospitals and general hospitals. A significant negative association was observed to exist between the total LOS (relative median LOS 0,974, CI 95% 0.959-0,989) of patients treated in advanced EMR hospitals (high EMRAM score cohort) versus patients treated at less advanced EMR care settings, once the data was adjusted for the case mix, year of surgery and type of surgery (laparoscopy or laparotomy). Adjusting for complications in a subgroup of general hospitals (n = 39) yielded essentially the same results (relative median LOS 0,934, CI 95% 0,915-0,954). No consistent significant associations were found with respect to LOS on the ICU. The findings of this study suggest advanced EMR capabilities support a healthcare provider's efforts to achieve desired quality outcomes and efficiency in Western European hospitals.
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http://dx.doi.org/10.1007/s10916-017-0734-3 | DOI Listing |
Neural Netw
September 2025
School of Electronic Science and Engineering, Nanjing University, China. Electronic address:
The Segment Anything Model (SAM) is a cornerstone of image segmentation, demonstrating exceptional performance across various applications, particularly in autonomous driving and medical imaging, where precise segmentation is crucial. However, SAM is vulnerable to adversarial attacks that can significantly impair its functionality through minor input perturbations. Traditional techniques, such as FGSM and PGD, are often ineffective in segmentation tasks due to their reliance on global perturbations that overlook spatial nuances.
View Article and Find Full Text PDFNeural Netw
September 2025
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China. Electronic address:
Automatic segmentation of retinal vessels from retinography images is crucial for timely clinical diagnosis. However, the high cost and specialized expertise required for annotating medical images often result in limited labeled datasets, which constrains the full potential of deep learning methods. Recent advances in self-supervised pretraining using unlabeled data have shown significant benefits for downstream tasks.
View Article and Find Full Text PDFNeural Netw
September 2025
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
3D shape defect detection plays an important role in autonomous industrial inspection. However, accurate detection of anomalies remains challenging due to the complexity of multimodal sensor data, especially when both color and structural information are required. In this work, we propose a lightweight inter-modality feature prediction framework that effectively utilizes multimodal fused features from the inputs of RGB, depth and point clouds for efficient 3D shape defect detection.
View Article and Find Full Text PDFParkinsonism Relat Disord
September 2025
Translational and Clinical Research Institute, Newcastle University, UK.
Introduction: Dysfunction of the glymphatic system is thought to lead to build up of toxic proteins including β-amyloid and α-synuclein, and thus may be involved in dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). The Diffusion Tensor Image Analysis Along the Perivascular Space (DTI-ALPS) index has been proposed as a marker of glymphatic function.
Aims: To investigate DTI-ALPS in mild cognitive impairment (MCI) and dementia, and determine its relationship with cognitive decline, and biomarkers of neurodegeneration.
Eur J Oncol Nurs
August 2025
Koç University Hospital, Faculty of Medicine, Department of Medical Oncology, Istanbul, Türkiye. Electronic address:
Purpose: This study aimed to evaluate the effectiveness of a mobile chemotherapy drug guide application, ChemoNurse, developed for cancer nurses, in improving their knowledge and attitudes toward chemotherapy practices.
Methods: A randomized controlled trial with a repeated-measures design was conducted with 59 nurses (29 intervention, 30 control) who participated. Nurses in the intervention group used the ChemoNurse mobile application for six months, while the control group received no additional intervention.