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2022 Advances in Science and engineering Technology International Conferences, ASET 2022

作者： Alshrbaji, Mohammad Mohammed, Maryam Shamayleh, Abdulrahim American University of Sharjah Biomedical Engineering Graduate program College of Engineering Sharjah United Arab Emirates University of Sharjah College of Engineering American Industrial Engineering Department Sharjah United Arab Emirates

ISBN: (纸本)9781665418010

The main goal of Total Quality Management (TQM) and Perceived Service Quality (PSQ) in the healthcare sector is to provide high-quality care to patients to meet their needs and expectation. Even in very unique circumstances like the COVID-19 outbreak, there is a need to evaluate how much the prementioned approaches affect patient satisfaction. However, patient satisfaction requires a proper synchronization between what the patient value and what the management perceives. In addition, there should be a focus on what impact the dimensions of TQM and PCQ have on patient satisfaction. As a result, studies have been conducted to identify what the patients value the most related to PSQ and TQM by designing and distributing questionnaires to a sample of patients and analyzing their responses. In this study, a review is conducted of empirical studies from various databases covering the period between 2008 and 2021. The objective is to analyze the influence of TQM and PSQ dimensions on patient satisfaction in healthcare organizations. © 2022 IEEE.

关键词： Health care

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Temperature-Dependent Hydrogen Modulations of Ultra-Scaled a-IGZO Thin Film Transistor Under Gate Bias Stress

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2024年 5卷 9-16页

作者： Aslam, Muhammad Chang, Shu-Wei Chuang, Min-Hui Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan701401 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Recently, a-IGZO has advanced toward the next-generation electronics system because of its compatibility with complementary metal oxide semiconductor (CMOS) and back-end-of-line (BOEL) based systems. A systematic electrical characterization of a-IGZO TFT related to reliability issues, such as positive bias temperature stress (PBTS) and negative bias temperature stress (NBTS), would entitle its integration into novel electronics systems. Unexpectedly, PBTS is characterized by the transition of positive Vth shift to negative Vth shift (ΔVth, the positive shift followed by the stress and temperature activated negative shift). This transition is attributed to charge trapping/trap-site generations and hydrogen migration to the active layer. The ΔVth shift mechanism depends on the temperature and voltage stress. On the other hand, a negative ΔVth shift has been observed during the NBTS operation and could be attributed to the hole trapping at the interface of GI/IGZO. An effective suppression of the gate leakage current has also been observed during reliability tests. Simulation results reveal a pronounced potential at the edges of source and drain regions, and considered the origin of hydrogen migration into the IGZO layer. Thermal image results also reveal the strong temperature/potential distribution at the edges of the source/drain regions, indorsing the simulation results. © 2020 IEEE.

关键词： Oxide semiconductors

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Spectral Learning of Shared Dynamics Between Generalized-Linear Processes 38

Spectral Learning of Shared Dynamics Between Generalized-Lin...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Oganesian, Lucine L. Sani, Omid G. Shanechi, Maryam M. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Ming Hsieh Department of Electrical and Computer Engineering Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los AngelesCA United States

Generalized-linear dynamical models (GLDMs) remain a widely-used framework within neuroscience for modeling time-series data, such as neural spiking activity or categorical decision outcomes. Whereas the standard usage of GLDMs is to model a single data source, certain applications require jointly modeling two generalized-linear time-series sources while also dissociating their shared and private dynamics. Most existing GLDM variants and their associated learning algorithms do not support this capability. Here we address this challenge by developing a multi-step analytical subspace identification algorithm for learning a GLDM that explicitly models shared vs. private dynamics within two generalized-linear time-series. In simulations, we demonstrate our algorithm's ability to dissociate and model the dynamics within two time-series sources while being agnostic to their respective observation distributions. In neural data, we consider two specific applications of our algorithm for modeling discrete population spiking activity with respect to a secondary time-series. In both synthetic and real data, GLDMs learned with our algorithm more accurately decoded one time-series from the other using lower-dimensional latent states, as compared to models identified using existing GLDM learning algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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A virtual positioning system for external beam radiotherapy

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Virtual Reality 2023年第3期27卷 2569-2582页

作者： Sung, Wen-Hsu Jiang, Ching-Fen Su, Tai-Sin Sun, Shuh-Ping Department of Physical Therapy and Assistive Technology National Yang Ming Chiao Tung University Taipei Taiwan Graduate Program of Smart Healthcare and Bioinformatics I-Shou University Kaohsiung Taiwan Department of Biomedical Engineering I-Shou University Kaohsiung Taiwan Department of Digital Media Design I-Shou University Kaohsiung Taiwan

In radiation therapy, positioning patients to ensure the accuracy of the setup of a procedure is a routine and labour-intensive process that substantially determines the efficacy of treatment. In this study, we propose a virtual positioning system that can simulate the positioning process with a visible beam path under the broad view of a life-like patient-positioning platform to obviate problems with excessively narrow view. This system integrates image processing, computer graphics, and virtual reality to encompass a 3D treatment target reconstructed from medical images of different modalities in a virtual scene. An innovative evaluation method is further proposed to verify the efficacy of the system using a full-scale 3D solid anthropometric model, and a treatment target showed an accuracy of 99% in calibration and a mean compatibility of 95% with an actual measurement. The proposed virtual positioning system provides a training and education platform for radiation therapy. The methodology through which the system was developed is also disclosed as a promising approach to improve the efficiency and safety of the position verification process for existing systems. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

关键词： Radiotherapy

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Feasibility Study of a Teleoperation System With Haptics for Tip-Force Sensing Active Needles

Feasibility Study of a Teleoperation System With Haptics for...

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IEEE/RAS-EMBS International Conference on biomedical Robotics and Biomechatronics (BioRob)

作者： Sooyeon Kim Sujin Yu Yuri Lim Suhyun Lee Seok Chang Ryu Department of Mechanical and Biomedical Engineering BioRobotics Laboratory Graduate Program in Smart Factory Ewha Womans University Seoul South Korea Department of Mechanical and Biomedical Engineering BioRobotics Laboratory Ewha Womans University

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

This paper presents the design of a teleoperation system with a haptic display for the active needles with tip-force sensing and tip-steering capabilities. The active needle design employs sensorized tendons by fiber Bragg gratings sensor (FBGs), while the teleoperation system combines a general haptic interface with electrical stimulation as its steering interface, delivering not only general force feedback but also tip-force information measured by the FBGs-based tendons to the operators. The essential features, such as tip-force sensing, teleoperation of the tip-joint, and human perception of the measured tip-force, were experimentally evaluated with their prototypes in tissue phantoms. Based on the results obtained, necessary follow-up studies were identified and suggested for the effective teleoperation of force-sensing steerable instruments in clinical environments. If successfully developed, such systems can enable surgeons to perceive clinical situations and perform operations more precisely and safely.

关键词： Instruments Surgery Prototypes Phantoms biomedical measurement Robot sensing systems Needles Fiber gratings Sensors Tendons

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Lung Nodule Analysis in CT Images: Deep Learning for Segmentation and Measurement 24

Lung Nodule Analysis in CT Images: Deep Learning for Segment...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Li, Ai-Hsien Adams Aruperes, Cristian Daniel Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Division of Cardiology Far Eastern Memorial Hospital New Taipei TaiwanGraduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanGraduate Institute of Medicine Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400716874

In the realm of research, the global health challenge posed by lung cancer remains pronounced, contributing substantially to annual cancer-related fatalities. The critical imperative lies in the early identification of pulmonary nodules, frequently indicative of impending lung cancer, to enhance patient outcomes and diminish mortality rates. Computed Tomography (CT) imaging stands out as a pivotal diagnostic instrument for the timely detection of these nodules. The swift proliferation of medical imaging data has underscored the pressing necessity for precise and efficient methodologies dedicated to nodule segmentation and measurement. These approaches are crucial in assisting radiologists in their diagnostic and clinical decision-making endeavors. In this study, we introduced a thorough method for analyzing lung nodules, leveraging dataset from Far Eastern Memorial Hospital (FEMH) comprising original CT images and manually annotated ground truth masks obtained with the assistance of radiologists at FEMH. This dataset is utilized for the segmentation of nodules. We employed advanced deep learning models, specifically the U-Net architecture, identified as the optimal model through our training process. We made substantial progress in nodule segmentation, attaining an Intersection over Union (IoU) score of 0.824 and a Dice Coefficient of 0.903 for the FEMH dataset. Furthermore, our performance improved when utilizing the merged dataset comprising FEMH and Luna16, yielding an IoU score of 0.862 and a Dice Coefficient of 0.926. Luna16 has been extensively utilized in numerous studies related to nodule detection and segmentation. In the next phase of the study, the best-performing model from our segmentation phase was utilized to predict nodule masks on the merged dataset. Subsequently, we measured the size of each predicted nodule by comparing it with the size ground truth mask in millimeters. In detail, this study achieved the Pearson Correlation Coefficient (PCC) at 0.

关键词： Computerized tomography

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A Simple Microfluidic Redox Cycling-Based Device for High-Sensitive Detection of Dopamine Released from Pc12 Cells

SSRN

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SSRN 2023年

作者： Şen, Mustafa Avcı, İpek Department of Biomedical Engineering Izmir Katip Celebi University Izmir Turkey Department of Biomedical Engineering Graduate Program Izmir Katip Celebi University Izmir Turkey

Here, a microfluidic redox cycle-based chip device (MRECD) was fabricated for high-sensitive and selective electrochemical detection of dopamine (DA). Briefly, ITO electrodes, each with a 3x3 mm working area, were fabricated using photolithography and dry etching processes. ITO electrodes were then modified with AuNPs to increase sensitivity. To fabricate MRECD with AuNPs (AuNPs- MRECD), one AuNPs-ITO was mounted and fixed on top of another using a PET film spacer to define a microfluidic channel for solution delivery. The device was electrochemically characterized in comparison to a device made of bare ITO electrodes (B-MRECD). According to the results, AuNPs- MRECD showed better redox cycling efficiency than B-MRECD with an amplification factor (Af ) of 49.9 and a collection efficiency (Ce) of 98.97 %. AuNPs-MRECD was then tested for sensitive and selective detection of DA, in which case the device displayed an LOD of 27.9 M over a linear detection range of 50 to 1000 nM based on reduction current. Finally, the device was successfully applied to the detection of DA released from PC12 cells, suggesting that the device is a promising tool for evaluating dopaminergic cells and the effects of dopaminergic drugs. © 2023, The Authors. All rights reserved.

关键词： Redox reactions

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Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis 2nd

Assessing the Impact of Sociotechnical Harms in AI-Based ...

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2nd International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the International Conference on Medical Image Computing and Computer Assisted Interventions, MICCAI 2024

作者： Stanley, Emma A. M. Souza, Raissa Winder, Anthony J. Wilms, Matthias Pike, G. Bruce Dagasso, Gabrielle Nielsen, Christopher MacEachern, Sarah J. Forkert, Nils D. Biomedical Engineering Graduate Program University of Calgary Calgary Canada Department of Radiology University of Calgary Calgary Canada Hotchkiss Brain Institute University of Calgary Calgary Canada Alberta Children’s Hospital Research Institute University of Calgary Calgary Canada Department of Pediatrics University of Calgary Calgary Canada

ISBN: (纸本)9783031727863

Clinical decision-making and radiology will inevitably be transformed by artificial intelligence (AI) in the coming years. The rapid adoption of AI in this domain, and in other everyday applications, has brought an increased awareness of the potential impacts and negative consequences that may occur throughout the sociotechnical systems that these technologies are implemented in. In this paper, we review and apply a previously published taxonomy of the sociotechnical harms of AI to investigate how these harms could manifest during the development and clinical implementation of AI-based medical image analysis. Through an illustrative case study example on computer-aided diagnosis using brain magnetic resonance imaging, we demonstrate how performing impact assessments of sociotechnical harms can assist in operationalizing the medical ethics principle of non-maleficence, thereby guiding the ethical development and implementation of AI technologies in healthcare. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Medical imaging

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Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

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Self-supervised neural network for phase retrieval in QDPC microscopy

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Optics Express 2023年第12期31卷 19897-19908页

作者： Chen, Ying-Ju Vyas, Sunil Huang, Hsuan-Ming Luo, Yuan Institute of Medical Device and Imaging National Taiwan University Taipei10051 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10051 Taiwan YongLin Institute of Health National Taiwan University Taipei10051 Taiwan Program for Precision Health and Intelligent Medicine Graduate School of Advanced Technology National Taiwan University Taipei10051 Taiwan

Quantitative differential phase contrast (QDPC) microscope plays an important role in biomedical research since it can provide high-resolution images and quantitative phase information for thin transparent objects without staining. With weak phase assumption, the retrieval of phase information in QDPC can be treated as a linearly inverse problem which can be solved by Tikhonov regularization. However, the weak phase assumption is limited to thin objects, and tuning the regularization parameter manually is inconvenient. A self-supervised learning method based on deep image prior (DIP) is proposed to retrieve phase information from intensity measurements. The DIP model that takes intensity measurements as input is trained to output phase image. To achieve this goal, a physical layer that synthesizes the intensity measurements from the predicted phase is used. By minimizing the difference between the measured and predicted intensities, the trained DIP model is expected to reconstruct the phase image from its intensity measurements. To evaluate the performance of the proposed method, we conducted two phantom studies and reconstructed the micro-lens array and standard phase targets with different phase values. In the experimental results, the deviation of the reconstructed phase values obtained from the proposed method was less than 10% of the theoretical values. Our results show the feasibility of the proposed methods to predict quantitative phase with high accuracy, and no use of ground truth phase. © 2023 Optica Publishing Group.

关键词： Inverse problems

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