Article
Cardiac & Cardiovascular Systems
Jairo Rodriguez Padilla, Robert D. Anderson, Christian Joens, Stephane Masse, Abhishek Bhaskaran, Ahmed Niri, Patrick Lai, Mohammed Ali Azam, Geoffrey Lee, Edward Vigmond, Kumaraswamy Nanthakumar
Summary: This study compared the accuracy of two-dimensional (2D) and three-dimensional (3D) conduction velocity (CV) algorithms in heart models, and examined the influence of mapping resolution on the results. The findings showed that 2D CV was significantly higher than 3D CV, and increased as the resolution decreased.
Article
Physiology
Stephen Gaeta, Tristram D. Bahnson, Craig Henriquez
Summary: A new high-resolution method DELTA was developed to accurately measure local activation time (LAT) differences, showing better accuracy for LAT differences below 4 ms compared to standard methods. Computational modeling and clinical validation suggest the DELTA method can improve measurement accuracy for small LAT differences, potentially enhancing myocardial conduction velocity (CV) assessment at small spatial scales.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Physiology
Jimena G. Siles-Paredes, Christopher J. Crowley, Flavio H. Fenton, Neal Bhatia, Shahriar Iravanian, Italo Sandoval, Stefan Pollnow, Olaf Dossel, Joao Salinet, Ilija Uzelac
Summary: This study proposes a method for local CV calculation from optical mapping measurements, which can characterize electrical conductivity and infer the depth of ablation lesions, providing new insights for guided ablation therapies.
FRONTIERS IN PHYSIOLOGY
(2022)
Article
Multidisciplinary Sciences
Christopher O'Shea, James Winter, S. Nashitha Kabir, Molly O'Reilly, Simon P. Wells, Olivia Baines, Laura C. Sommerfeld, Joao Correia, Ming Lei, Paulus Kirchhof, Andrew P. Holmes, Larissa Fabritz, Kashif Rajpoot, Davor Pavlovic
Summary: Optical mapping is a widely used technique in pre-clinical cardiac research, allowing for efficient study of cardiac electrophysiology and the effects of interventions on arrhythmia.
Article
Cardiac & Cardiovascular Systems
Joshua Hawson, Robert D. Anderson, Ahmed Al-kaisey, David Chieng, Louise Segan, Troy Watts, Timothy Campbell, Joseph Morton, Alexander McLellan, Peter Kistler, Aleksander Voskoboinik, Bhupesh Pathik, Saurabh Kumar, Jonathan Kalman, Geoffrey Lee
Summary: This study describes the utility of automated conduction velocity mapping (ACVM) in ventricular tachycardia (VT) ablation. ACVM can accurately resolve complex VT circuits and identify slow conduction zones, but its accuracy is limited in substrate-based mapping.
JACC-CLINICAL ELECTROPHYSIOLOGY
(2022)
Article
Cardiac & Cardiovascular Systems
Mathijs S. van Schie, Nawin L. Ramdat Misier, Payam Razavi Ebrahimi, Annejet Heida, Rohit K. Kharbanda, Yannick J. H. J. Taverne, Natasja M. S. de Groot
Summary: Loss of cell-to-cell communication leads to local conduction disorders and directional heterogeneity (LDH) in conduction velocity (CV) vectors, which can be revealed by premature atrial contractions (PACs). This study quantified LDH and compared the differences between sinus rhythm (SR) and PACs in patients with and without atrial fibrillation (AF). The results showed that LDH increased during PACs, especially at Bachmann's bundle (BB) and pulmonary vein area (PVA). Patients with AF already had more LDH during SR, and this heterogeneity became more pronounced during PACs.
Article
Cardiac & Cardiovascular Systems
Dandan Yang, Xiaoping Wan, Adrienne T. Dennis, Emre Bektik, Zhihua Wang, Mauricio G. S. Costa, Charline Fagnen, Catherine Venien-Bryan, Xianyao Xu, Daniel H. Gratz, Thomas J. Hund, Peter J. Mohler, Kenneth R. Laurita, Isabelle Deschenes, Ji-Dong Fu
Summary: This study reveals a novel biophysical action of endogenous miRs in modulating cardiac electrophysiology through noncanonical mechanisms. Endogenous miR1 physically binds with cardiac membrane protein Kir2.1, suppressing I-K1 and affecting action potential of cardiomyocytes. The findings suggest that miRs may be involved in the pathogenesis of cardiac arrhythmias by regulating ion channel physiology and pathology.
Review
Cell Biology
Sander Verheule, Ulrich Schotten
Summary: Fibrosis is recognized as a key determinant of conduction disturbances in both atria and ventricles, with different forms such as replacement, endomysial, perimysial, perivascular, endocardial, and epicardial fibrosis. The impact on conduction depends on how the patterns of electrical connections between myocytes are altered. Evaluating cardiac fibrosis should exclude fibrous tissue that does not affect conduction and differentiate between different types.
Article
Medicine, General & Internal
Andrea Frustaci, Romina Verardo, Matteo Antonio Russo, Marina Caldarulo, Maria Alfarano, Nicola Galea, Fabio Miraldi, Cristina Chimenti
Summary: This study reports the correlation between conduction tissue pathology and arrhythmias in patients with cardiac amyloidosis. The degree of conduction tissue infiltration was found to be correlated with ventricular arrhythmias, maximal wall thickness, and type of amyloid protein. The results suggest that amyloid-associated cardiac arrhythmias are related to the extent of conduction tissue infiltration, which is independent of the type and severity of amyloidosis.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Medicine, General & Internal
Annejet Heida, Mathijs S. van Schie, Willemijn F. B. van der Does, Yannick J. H. J. Taverne, Ad J. J. C. Bogers, Natasja M. S. de Groot
Summary: This case-control study compared atrial conduction velocity (CV) in patients with and without atrial fibrillation (AF). The study found no significant difference in biatrial CV between the two groups, except for a reduction in CV in the Bachmann's bundle (BB) area in the AF group. AF was associated with prolonged total activation times and decreased voltages at BB, indicating a potential role of BB in AF development and maintenance.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Multidisciplinary Sciences
Michael Rieger, Christian Dellenbach, Johannes vom Berg, Jane Beil-Wagner, Ange Maguy, Stephan Rohr
Summary: The POEMS system is a panoramic opto-electrical measurement and stimulation system that allows flexible combinations of optical and electrical recording and stimulation modalities for investigating cardiac function. Composed of 294 optical fibers and 64 electrodes forming a cup covering the entire ventricular surface of mouse hearts, the system enables straightforward 'drop&go' experimentation.
NATURE COMMUNICATIONS
(2021)
Article
Engineering, Biomedical
Lucas A. Woodworth, Baris Cansiz, Michael Kaliske
Summary: Conduction velocity error is a major issue in cardiac electrophysiology that requires high computational effort and fine spatial discretization. This study introduces a novel approach using a modified quadrature method to simulate accurate conduction velocity in coarse meshes with linear elements. Numerical experiments demonstrate the effectiveness of this approach under different discretization and conductivity conditions, showing improved accuracy in wave propagation. However, the method is limited to specific linear elements and may experience reduced accuracy in irregular meshes and with heterogeneous conductivities.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
(2022)
Article
Biochemistry & Molecular Biology
Ting- Lee, Nguyen Ngoc Trang, Ting-Wei Lee, Satoshi Higa, Yu-Hsun Kao, Yao-Chang Chen, Yi-Jen Chen
Summary: A ketogenic diet may attenuate the effects of diabetic cardiomyopathy by regulating sodium and calcium homeostasis.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Physiology
Steven E. Williams, Caroline H. Roney, Adam Connolly, Iain Sim, John Whitaker, Daniel O'Hare, Irum Kotadia, Louisa O'Neill, Cesare Corrado, Martin Bishop, Steven A. Niederer, Matt Wright, Mark O'Neill, Nick W. F. Linton
Summary: OpenEP framework has been developed to evaluate electroanatomic mapping data, providing core functionality for conducting such research. It is space-efficient and accurately represents the original data. OpenEP captures the majority of data required for contemporary electroanatomic mapping-based electrophysiology research and offers a roadmap for future development.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Cardiac & Cardiovascular Systems
David E. Krummen, Christopher T. Villongco, Gordon Ho, Amir A. Schricker, Michael E. Field, Kevin Sung, Katherine A. Kacena, Melissa S. Martinson, Kurt S. Hoffmayer, Jonathan C. Hsu, Farshad Raissi, Gregory K. Feld, Andrew D. McCulloch, Frederick T. Han
Summary: The study evaluated the accuracy of noninvasive arrhythmia source localization using a computational mapping system, showing that it exceeded prespecified goals for locating atrial and ventricular arrhythmias. Spatial accuracy analysis demonstrated clinically actionable results, suggesting the potential for rapid, noninvasive mapping technology to aid in targeted arrhythmia therapies.
CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY
(2022)
Article
Biotechnology & Applied Microbiology
Mehwish Arshad, Shuyu Cheng, Maarten van Reeuwijk, Spencer J. Sherwin, Peter D. Weinberg
Summary: Simple alterations were made in the swirling well method to alleviate the issues associated with shear flow. Numerical simulation was used to obtain flows, and various modifications were tested to achieve similar flow conditions and separate different shear metrics. These improvements overcome the limitations of the baseline model.
BIOTECHNOLOGY AND BIOENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Mohsen Lahooti, Yan Bao, David Scott, Rafael Palacios, Spencer J. Sherwin
Summary: Nektar++ is an open-source framework for constructing low-order and high-order finite element solvers using the spectral/hp element method. It provides an efficient and flexible platform for developing solvers for partial differential equations. In this study, Nektar++ is used to develop two fluid-structure interaction solvers for highly deformable nonlinear slender structures, demonstrating its capabilities.
COMPUTER PHYSICS COMMUNICATIONS
(2023)
Article
Cardiac & Cardiovascular Systems
Nadine Ali, Ahran D. Arnold, Alejandra A. Miyazawa, Daniel Keene, Ji-Jian Chow, Ian Little, Nicholas S. Peters, Prapa Kanagaratnam, Norman Qureshi, Fu Siong Ng, Nick W. F. Linton, David C. Lefroy, Darrel P. Francis, Phang Boon Lim, Mark A. Tanner, Amal Muthumala, Matthew J. Shun-Shin, Graham D. Cole, Zachary Whinnett
Summary: This study compared the physiological effectiveness of left bundle branch area pacing (LBBAP) and His bundle pacing (HBP) in cardiac resynchronization therapy (CRT), and found that HBP showed better ventricular resynchronization than LBBAP. However, LBBAP was not inferior to HBP in left ventricular electrical resynchronization and acute hemodynamic response.
Letter
Cardiac & Cardiovascular Systems
Arunashis Sau, Fu Siong Ng
Article
Computer Science, Interdisciplinary Applications
Ganlin Lyu, Chao Chen, Xi Du, Spencer J. Sherwin
Summary: One approach to reduce the computational cost of simulating transitional compressible boundary layer flow is to use a reduced domain with compatible boundary conditions enforced with a computationally cheaper RANS simulation. It is important to maintain entropy compatibility with the RANS simulation for a stable solution. The entropy-pressure enforcement is the only stable boundary condition that can enforce a known pressure distribution, but a mix of inflow boundary conditions is needed in the region near the stagnation point.
JOURNAL OF COMPUTATIONAL PHYSICS
(2023)
Review
Neurosciences
Vineesh Kappadan, Anies Sohi, Ulrich Parlitz, Stefan Luther, Ilija Uzelac, Flavio Fenton, Nicholas S. Peters, Jan Christoph, Fu Siong Ng
Summary: Optical mapping is a commonly used tool in studying the electrophysiological properties of myocardial preparations. However, motion artifact from myocardial contraction poses a challenge to performing optical mapping on contracting hearts. Recent advancements in computer vision algorithms and ratiometric techniques have allowed for optical mapping studies on contracting hearts. This review discusses the techniques and challenges of optical mapping on contracting hearts.
JOURNAL OF PHYSIOLOGY-LONDON
(2023)
Article
Cardiac & Cardiovascular Systems
Maddalena Ardissino, Eric A. W. Slob, Paul Carter, Tormod Rogne, Joanna Girling, Stephen Burgess, Fu Siong Ng
Summary: This study used Mendelian randomization to explore the causal relevance of reproductive factors on cardiovascular disease in women. The results showed that earlier genetically predicted age at first birth, higher genetically predicted number of live births, and earlier genetically predicted age at menarche were associated with increased risk of cardiovascular disease. These findings support the role of reproductive factors in the development of cardiovascular disease in women and identify potential modifiable mediators for clinical intervention.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2023)
Article
Cardiac & Cardiovascular Systems
Hans F. Stabenau, Arunashis Sau, Daniel B. Kramer, Nicholas S. Peters, Fu Siong Ng, Jonathan W. Waks
Summary: The spatial ventricular gradient (SVG), spatial QRST angles, and other vector cardio graphic measures of myocardial electrical heterogeneity have been studied as novel risk stratification methods for sudden cardiac death and other adverse cardiovascular events. However, the normal limits and the influence of factors such as age, race, and BMI on these measurements are still unclear.
JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY
(2023)
Article
Mechanics
An-Kang Gao, Chris D. Cantwell, Onur Son, Spencer J. Sherwin
Summary: In this study, the three-dimensional transition and force characteristics of plunging airfoils are investigated using experimental measurements, numerical simulations, and linear stability analysis. The interaction between the leading-edge vortex (LEV), the previous-cycle LEV (pLEV), and the trailing-edge vortex (TEV) is found to be the primary factor affecting the 3-D transition and associated forces. The results show that different interaction patterns and vortex pairs have different effects on the stability and lift of the LEV, depending on the range of the chord-based Strouhal number St(c).
JOURNAL OF FLUID MECHANICS
(2023)
Article
Peripheral Vascular Disease
Maddalena Ardissino, Rohin K. K. Reddy, Eric A. W. Slob, Jack Griffiths, Joanna Girling, Fu Siong Ng
Summary: This study used Mendelian randomization to investigate the causal relevance of hypertensive indices in adverse pregnancy outcomes. The results showed that higher systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) were associated with preeclampsia or eclampsia, preterm birth, and placental abruption. SBP and PP had the strongest associations with multiple adverse outcomes.
JOURNAL OF HYPERTENSION
(2023)
Article
Cardiac & Cardiovascular Systems
Nadine Ali, Ahran D. Arnold, Alejandra A. Miyazawa, Daniel Keene, Nicholas S. Peters, Prapa Kanagaratnam, Norman Qureshi, Fu Siong Ng, Nick W. F. Linton, David C. Lefroy, Darrel P. Francis, Phang Boon Lim, Peter Kellman, Mark A. Tanner, Amal Muthumala, Matthew Shun-Shin, Zachary I. Whinnett, Graham D. Cole
Summary: The presence of septal scar can affect the success rate of left bundle branch area pacing, and alternative approaches or implant tools may be needed to overcome this issue.
PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY
(2023)
Review
Multidisciplinary Sciences
Mario Lino, Stathi Fotiadis, Anil A. Bharath, Chris D. Cantwell
Summary: In the past decade, deep learning has made rapid progress and developed powerful tools for automating traditionally complex tasks such as image synthesis and natural language processing. In the context of simulating fluid dynamics, novel deep learning methods have been developed to replace or enhance traditional numerical solvers. These methods can be classified into physics-driven and data-driven approaches, with physics-driven methods aiming to provide analytical solutions to fluid dynamics problems by minimizing residuals, and data-driven methods providing fast and approximate solutions based on observed physical properties. The symbiosis of numerical solvers and deep learning has also shown promise in turbulence modeling and accelerating iterative solvers, although challenges still exist, such as extrapolation issues and difficulties in training against turbulent flows. Efforts are being made to improve the current state of the art.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Meeting Abstract
Biophysics
Caroline Koch, Benedict Reilley-O'Donnell, Richard Gutierrez, Carla Lucarelli, Fu Siong Ng, Julia Gorelik, Aleksandar P. Ivanov, Joshua B. Edel
EUROPEAN BIOPHYSICS JOURNAL WITH BIOPHYSICS LETTERS
(2023)
Meeting Abstract
Obstetrics & Gynecology
Maddalena Ardissino, Rohin Reddy, Eric Slob, Jack Griffiths, Joanna Girling, Fu Siong Ng
BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY
(2023)
Article
Cardiac & Cardiovascular Systems
Charles Butcher, Caroline Roney, Amy Wharmby, Nikhil Ahluwalia, Anthony Chow, Pier D. Lambiase, Ross J. Hunter, Shohreh Honarbakhsh
Summary: This study evaluated different methods for assessing atrial voltage and their accuracy in identifying pulmonary vein reconnection sites (PVRSs) in atrial fibrillation (AF). The results showed that omnipoar voltage atrial fibrillation (OV AF) maps improve voltage assessment by overcoming the impact of wavefront collision and fractionation, leading to improved accuracy.
JACC-CLINICAL ELECTROPHYSIOLOGY
(2023)
Article
Biology
Seyyed Bahram Borgheai, Alyssa Hillary Zisk, John McLinden, James Mcintyre, Reza Sadjadi, Yalda Shahriari
Summary: This study proposed a novel personalized scheme using fNIRS and EEG as the main tools to predict and compensate for the variability in BCI systems, especially for individuals with severe motor deficits. By establishing predictive models, it was found that there were significant associations between the predicted performances and the actual performances.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hongliang Guo, Hanbo Liu, Ahong Zhu, Mingyang Li, Helong Yu, Yun Zhu, Xiaoxiao Chen, Yujia Xu, Lianxing Gao, Qiongying Zhang, Yangping Shentu
Summary: In this paper, a BDSMA-based image segmentation method is proposed, which improves the limitations of the original algorithm by combining SMA with DE and introducing a cooperative mixing model. The experimental results demonstrate the superiority of this method in terms of convergence speed and precision compared to other methods, and its successful application to brain tumor medical images.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jingfei Hu, Linwei Qiu, Hua Wang, Jicong Zhang
Summary: This study proposes a novel semi-supervised point consistency network (SPC-Net) for retinal artery/vein (A/V) classification, addressing the challenges of specific tubular structures and limited well-labeled data in CNN-based approaches. The SPC-Net combines an AVC module and an MPC module, and introduces point set representations and consistency regularization to improve the accuracy of A/V classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes
Summary: This study introduces a novel hybrid model called ConTraNet, which combines the strengths of CNN and Transformer neural networks, and achieves significant improvement in classification performance with limited training data.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Juan Antonio Valera-Calero, Dario Lopez-Zanoni, Sandra Sanchez-Jorge, Cesar Fernandez-de-las-Penas, Marcos Jose Navarro-Santana, Sofia Olivia Calvo-Moreno, Gustavo Plaza-Manzano
Summary: This study developed an easy-to-use application for assessing the diagnostic accuracy of digital pain drawings (PDs) compared to the classic paper-and-pencil method. The results demonstrated that digital PDs have higher reliability and accuracy compared to paper-and-pencil PDs, and there were no significant differences in assessing pain extent between the two methods. The PAIN EXTENT app showed good convergent validity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Biao Qu, Jialue Zhang, Taishan Kang, Jianzhong Lin, Meijin Lin, Huajun She, Qingxia Wu, Meiyun Wang, Gaofeng Zheng
Summary: This study proposes a deep unrolled neural network, pFISTA-DR, for radial MRI image reconstruction, which successfully preserves image details using a preprocessing module, learnable convolution filters, and adaptive threshold.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Alireza Rafiei, Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran
Summary: This study aimed to improve machine learning model prediction of fluid overload by integrating synthetic data, which could be translated to other clinical outcomes.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jinlian Ma, Dexing Kong, Fa Wu, Lingyun Bao, Jing Yuan, Yusheng Liu
Summary: In this study, a new method based on MDenseNet is proposed for automatic segmentation of nodular lesions from ultrasound images. Experimental results demonstrate that the proposed method can accurately extract multiple nodules from thyroid and breast ultrasound images, with good accuracy and reproducibility, and it shows great potential in other clinical segmentation tasks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jiabao Sheng, SaiKit Lam, Jiang Zhang, Yuanpeng Zhang, Jing Cai
Summary: Omics fusion is an important preprocessing approach in medical image processing that assists in various studies. This study aims to develop a fusion methodology for predicting distant metastasis in nasopharyngeal carcinoma by mitigating the disparities in omics data and utilizing a label-softening technique and a multi-kernel-based neural network.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Zhenxiang Xiao, Liang He, Boyu Zhao, Mingxin Jiang, Wei Mao, Yuzhong Chen, Tuo Zhang, Xintao Hu, Tianming Liu, Xi Jiang
Summary: This study systematically investigates the functional connectivity characteristics between gyri and sulci in the human brain under naturalistic stimulus, and identifies unique features in these connections. This research provides novel insights into the functional brain mechanism under naturalistic stimulus and lays a solid foundation for accurately mapping the brain anatomy-function relationship.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qianqian Wang, Mingyu Zhang, Aohan Li, Xiaojun Yao, Yingqing Chen
Summary: The development of PARP-1 inhibitors is crucial for the treatment of various cancers. This study investigates the structural regulation of PARP-1 by different allosteric inhibitors, revealing the basis of allosteric inhibition and providing guidance for the discovery of more innovative PARP-1 inhibitors.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qing Xu, Wenting Duan
Summary: In this paper, a dual attention supervised module, named DualAttNet, is proposed for multi-label lesion detection in chest radiographs. By efficiently fusing global and local lesion classification information, the module is able to recognize targets with different sizes. Experimental results show that DualAttNet outperforms baselines in terms of mAP and AP50 with different detection architectures.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Kaja Gutowska, Piotr Formanowicz
Summary: The primary aim of this research is to propose algorithms for identifying significant reactions and subprocesses within biological system models constructed using classical Petri nets. These solutions enable two analysis methods: importance analysis for identifying critical individual reactions to the model's functionality and occurrence analysis for finding essential subprocesses. The utility of these methods has been demonstrated through analyses of an example model related to the DNA damage response mechanism. It should be noted that these proposed analyses can be applied to any biological phenomenon represented using the Petri net formalism. The presented analysis methods extend classical Petri net-based analyses, enhancing our comprehension of the investigated biological phenomena and aiding in the identification of potential molecular targets for drugs.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Heejung Choi, Ha Na Cho, Minkyoung Kim, Jiye Han, Gaeun Kee, Seohyun Park, Kye Hwa Lee, Tae Joon Jun, Young-Hak Kim
Summary: Electronic medical records have potential in advancing healthcare technologies, but privacy issues hinder their full utilization. Deep learning-based generative models can mitigate this problem by creating synthetic data similar to real patient data. However, the risk of data leakage due to malicious attacks poses a challenge to traditional generative models. To address this, we propose a method that employs local differential privacy (LDP) to protect the model from attacks and preserve the privacy of training data, while generating medical data with reasonable performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Siwei Tao, Zonghan Tian, Ling Bai, Yueshu Xu, Cuifang Kuang, Xu Liu
Summary: This study proposes a transfer learning-based method to address the phase retrieval problem in grating-based X-ray phase contrast imaging. By generating a training dataset and using deep learning techniques, this method improves image quality and can be applied to X-ray 2D and 3D imaging.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)