Article
Computer Science, Interdisciplinary Applications
Kyle Baylous, Ryan Helbock, Brandon Kovarovic, Salwa Anam, Marvin Slepian, Danny Bluestein
Summary: This study presents a computational analysis of fatigue in TAVR stents, revealing underestimated risks of fatigue failure in previous studies. Using a simulated beating heart model, different sections of the stents showed significant variations in fatigue resistance. The study demonstrates the potential of computational analysis in evaluating TAVR device durability.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Xihao Wang, Pengyue Liu, Sen Zhao, Fei Wang, Xiaodong Li, Lianqu Wang, Yongjun Yan, Guang-an Zou, Guoliang Xu
Summary: This study established a realistic model of the posterior urethra based on MRI data and urodynamic data of patients, and analyzed the urodynamic characteristics after BPH surgery using CFD dynamic simulation. The study found that the posterior urethral morphology has an important impact on the urinary flow characteristics, and can provide a basis for personalized surgical plans in the future.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Information Systems
R. F. Willemsen, J. J. Aardoom, O. P. van der Galien, S. van de Vijver, N. H. Chavannes, A. Versluis
Summary: This study evaluated healthcare usage and costs of patients using a digital platform, showing an increase in GP consultations and costs after implementation.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Xinhui Liu, Pan Song, Qi Gao, Min Dai, Junjie Rao, Jun Wen
Summary: This study investigated the hemodynamic effects of carotid webs (CWs) at different locations in the carotid arteries using numerical simulations, and found that CWs located at the origin of the internal carotid artery are more likely to cause disturbed blood flow patterns and thrombus formation, increasing the risk of ischemic stroke in distal cerebral arteries.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Xingyun Li, Xinyu Yi, Jiayu Ye, Yunshao Zheng, Qingxiang Wang
Summary: This study proposes an automatic depression detection method SFTNet based on microexpressions, and demonstrates its accuracy through emotional stimulation experiments and doctor-patient conversations. The method has significant implications for assisting doctors in diagnosing depression.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Information Systems
Sari Kujala, Saija Simola, Bo Wang, Hedvig Soone, Josefin Hagstrom, Annika Barkas, Iiris Horhammer, Asa Cajander, Asbjorn Johansen Fagerlund, Bridget Kane, Anna Kharko, Eli Kristiansen, Jonas Moll, Hanife Rexphepi, Maria Hagglund, Monika A. Johansen
Summary: This study benchmarks the usability of national patient portals in Estonia, Finland, Norway, and Sweden using a mixed-methods survey approach. The results indicate variations in usability across countries and highlight the influence of very positive and very negative experiences on usability ratings. The survey approach proves effective in evaluating user experiences and identifying areas for improvement and desirable features.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Alireza Karimi, Reza Razaghi, Siddharth Daniel D'costa, Saeed Torbati, Sina Ebrahimi, Seyed Mohammadali Rahmati, Mary J. Kelley, Ted S. Acott, Haiyan Gong
Summary: This study investigated the biomechanical properties of the conventional aqueous outflow pathway using fluid-structure interaction. The results showed that the distribution of aqueous humor wall shear stress within this pathway is not uniform, which may contribute to our understanding of the underlying selective mechanisms.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Chun-You Chen, Ya-Lin Chen, Jeremiah Scholl, Hsuan-Chia Yang, Yu-Chuan (Jack) Li
Summary: This study evaluated the overall performance of a machine learning-based CDSS (MedGuard) in triggering clinically relevant alerts and intercepting inappropriate drug errors and LASA drug errors. The results showed that MedGuard has the ability to improve patients' safety by triggering clinically valid alerts.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Review
Computer Science, Information Systems
Ivan Otero-Gonzalez, Moises R. Pacheco-Lorenzo, Manuel J. Fernandez-Iglesias, Luis E. Anido-Rifon
Summary: This study explores the applications of conversational agents in detecting mental health disorders, specifically depression screening. The findings indicate that conversational agents are effective in detecting depression, and voice interaction is the future direction of development.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Article
Computer Science, Information Systems
Muhammad Asaduzzaman, Zeleke Mekonnen, Ernst Kristian Rodland, Sundeep Sahay, Andrea Sylvia Winkler, Christoph Gradmann
Summary: Our study explored the perspectives of stakeholders in Jimma, Ethiopia on the use of DHIS2 as a One Health Antimicrobial Resistance (AMR) surveillance platform. The findings suggest that DHIS2 has the potential to be a user-friendly and acceptable platform for OH-AMR surveillance. Despite some challenges, most participants perceived DHIS2 as suitable for OH-AMR surveillance and expressed their willingness to contribute in their current professional roles.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Hao Sun, Bao Li, Jincheng Liu, Xiaolu Xi, Liyuan Zhang, Yanping Zhang, Guangfei Li, Huamei Guo, Kenan Gu, Tongna Wang, Chuanqi Wen, Youjun Liu
Summary: This study established a lumped-parameter model (BTM-LPM) of brain tissue microcirculation based on computed tomography angiography (CTA), which can accurately calculate cerebral perfusion in real time and demonstrate the importance of Circle of Willis anatomy in different ischemic injuries to cerebral tissue. The calculated cerebral perfusion would serve as a reference value for early diagnosis and preoperative planning of different ischemic injuries to cerebral tissue, showing great potential for replacing computed tomography perfusion (CTP) examination.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Hao Yu, Haoyu Liu, Zhe Liu, Zeyu Wang, Jiabin Jia
Summary: This study proposes a novel data-driven method called structure-aware hybrid-fusion learning (SA-HFL) for mining deep feature information from measurement voltages in electrical impedance tomography (EIT) and reconstructing high-resolution conductivity distribution. The results show that SA-HFL outperforms other deep learning networks and the IGGS method in qualitative and quantitative analyses, improving evaluation metrics such as relative error, mean structural similarity index, and peak signal-to-noise ratio. The proposed network also exhibits efficient execution with appropriate parameters and floating-point operations per second (FLOPs).
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Review
Computer Science, Information Systems
Sarang Hashemi, Lu Bai, Shijia Gao, Frada Burstein, Kate Renzenbrink
Summary: This study demonstrates the value of the MINDSPACE framework in designing clinical decision support alerts and reminders. The framework addresses the challenges faced by designers in identifying behavioral effects relevant to alert and reminder designs.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Robert V. Bergen, Jean-Francois Rajotte, Fereshteh Yousefirizi, Arman Rahmim, Raymond T. Ng
Summary: This article introduces a 3D generative model called TrGAN, which can generate medical images with important features and statistical properties while protecting privacy. By evaluating through a membership inference attack, the fidelity, utility, and privacy trade-offs of the model were studied.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Lingzhi Tang, Xueqi Wang, Jinzhu Yang, Yonghuai Wang, Mingjun Qu, HongHe Li
Summary: In this paper, a dynamical local feature fusion net for automatically recognizing aortic valve calcification (AVC) from echocardiographic images is proposed. The network segments high-echo areas and adjusts the selection of local features to better integrate global and local semantic representations. Experimental results demonstrate the effectiveness of the proposed approach.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
You-Lei Fu, Wu Song, Wanni Xu, Jie Lin, Xuchao Nian
Summary: This study investigates the combination of surface electromyographic signals (sEMG) and deep learning-based CNN networks to study the interaction between humans and products and the impact on body comfort. It compares the advantages and disadvantages of different CNN networks and finds that DenseNet has unique advantages over other algorithms in terms of accuracy and ease of training, while mitigating issues of gradient disappearance and model degradation.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala, Johannes Haubold, Felix Nensa, Kevin Kroeninger, Jan Egger, Jens Kleesiek
Summary: In this study, a deep learning-based skull stripping algorithm for MRI was proposed, which works directly in the complex valued k-space and preserves the phase information. The results showed that the algorithm achieved similar results to the ground truth, with higher accuracy in the slices above the eye region. This approach not only preserves valuable information for further diagnostics, but also enables immediate anonymization of patient data before being transformed into the image domain.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Information Systems
Pedro A. Moreno-Sanchez, Ruben Arroyo-Fernandez, Elisabeth Bravo-Esteban, Asuncion Ferri-Morales, Mark van Gils
Summary: This study analyzed data from fibromyalgia patients to assess the impact of mental health factors on fibromyalgia severity compared to pain factors. The findings suggest that mental health factors are more relevant for fibromyalgia severity.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Zelin Zhang, Sara Arabyarmohammadi, Patrick Leo, Howard Meyerson, Leland Metheny, Jun Xu, Anant Madabhushi
Summary: This article introduces a segmentation model based on conditional generative adversarial network for efficient segmentation of myeloblasts from slides of AML patients. Through validation experiments, it is confirmed that this method has better segmentation performance than other deep learning models, and prognostic models for predicting the risk of recurrence in AML patients have been constructed using the segmentation results.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Si Mu, Weizhao Lu, Guanghui Yu, Lei Zheng, Jianfeng Qiu
Summary: This study developed a WMHs risk prediction model that accurately evaluates the severity of WMHs and identifies potential high-risk regions in the entire brain. The validation results demonstrate that WMHs are associated with structural and functional alterations in the brain, as well as cognitive decline.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
