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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Zeeman polaritons as a platform for probing Dicke physics in condensed matter

arXiv

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arXiv 2024年

作者： Kritzell, T. Elijah Doumani, Jacques Asano, Tobias Yamada, Sota Tay, Fuyang Xu, Hongjing Yan, Han Katayama, Ikufumi Takeda, Jun Nevidomskyy, Andriy Nojiri, Hiroyuki Bamba, Motoaki Baydin, Andrey Kono, Junichiro Applied Physics Graduate Program Smalley-Curl Institute Rice University 6100 Main Street HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University 6100 Main Street HoustonTX77005 United States Department of Physics Yokohama National University 79-5 Tokiwadai Hodogaya-ku Kanagawa Yokohama240-8501 Japan Department of Physics and Astronomy Rice University 6100 Main Street HoustonTX77005 United States Smalley-Curl Institute Rice University 6100 Main Street HoustonTX77005 United States Institute for Multidisciplinary Sciences Yokohama National University 79-5 Tokiwadai Hodogaya-ku Kanagawa Yokohama240-8501 Japan Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba-ku Miyagi Sendai980-8577 Japan Rice Advanced Materials Institute Rice University 6100 Main Street HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University 6100 Main Street HoustonTX77005 United States

The interaction of an ensemble of two-level atoms and a quantized electromagnetic field, described by the Dicke Hamiltonian, is an extensively studied problem in quantum optics. However, experimental efforts to explore similar physics in condensed matter typically employ bosonic matter modes (e.g., phonons, magnons, and plasmons) that are describable as simple harmonic oscillators, i.e., an infinite ladder of equally spaced energy levels. Here, we examine ultrastrong coupling between a coherent light mode and an ensemble of paramagnetic spins, a finite-multilevel system, in Gd3Ga5O12. The electron paramagnetic resonance of Gd3+ ions is tuned by a magnetic field into resonance with a Fabry–Pérot cavity mode, resulting in the formation of spin–photon hybrid states, or Zeeman polaritons. We observe that the light–matter coupling strength, measured through the vacuum Rabi splitting, decreases with increasing temperature, which can be explained by the temperature-dependent population difference between the lower and higher-energy states, a trait of a finite-level system. This finding demonstrates that a spin–boson system is more compatible with the Dicke model and has advantages over boson–boson systems for pursuing experimental realizations of phenomena predicted for ultrastrongly coupled light–matter hybrids. Copyright © 2024, The Authors. All rights reserved.

关键词： Phonons

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Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Muhammad Iqbal Dahlan Abdullah H Hartono Cut Ita Erliana S Sriadhi Nurmawati M Adhi Prasnowo Abdurrozzaq Hasibuan Akbar Iskandar Kundharu Saddhono Abdussakir Hastuti Musa Muhammad Ikhsan Setiawan Youmeni Sagala Rumiris Siahaan Eka Mayastika Sinaga Anggraini Syahputri Feby Milanie Henry Aspan Muammar Khaddafi Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan-Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods.

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Retraction: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method (J. Phys.: Conf. Ser. 1114 012082)

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Journal of Physics: Conference Series 2018年第1期1114卷

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

arXiv

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arXiv 2021年

作者： Hering, Alessa Hansen, Lasse Mok, Tony C.W. Chung, Albert C.S. Siebert, Hanna Häger, Stephanie Lange, Annkristin Kuckertz, Sven Heldmann, Stefan Shao, Wei Vesal, Sulaiman Rusu, Mirabela Sonn, Geoffrey Estienne, Théo Vakalopoulou, Maria Han, Luyi Huang, Yunzhi Yap, Pew-Thian Brudfors, Mikael Balbastre, Yaël Joutard, Samuel Modat, Marc Lifshitz, Gal Raviv, Dan Lv, Jinxin Li, Qiang Jaouen, Vincent Visvikis, Dimitris Fourcade, Constance Rubeaux, Mathieu Pan, Wentao Xu, Zhe Jian, Bailiang De Benetti, Francesca Wodzinski, Marek Gunnarsson, Niklas Sjölund, Jens Grzech, Daniel Qiu, Huaqi Li, Zeju Thorley, Alexander Duan, Jinming Großbröhmer, Christoph Hoopes, Andrew Reinertsen, Ingerid Xiao, Yiming Landman, Bennett Huo, Yuankai Murphy, Keelin Lessmann, Nikolas van Ginneken, Bram Dalca, Adrian V. Heinrich, Mattias P. Institute of Medical Informatics Universität zu Lübeck Ratzeburger Allee 160 Lübeck23562 Germany Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany Department of Radiology and Nuclear Medicine Radboud University Medical Center GA Nijmegen6525 Netherlands The Institute of Medical Informatics Universität zu Lübeck Lübeck23562 Germany The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong The Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany The Department of Radiology Stanford University StanfordCA94305 United States The Department of Urology Stanford University StanfordCA94305 United States The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette 91190 France Université Paris-Saclay Institut Gustave Roussy Inserm Radiothérapie Moléculaire et Innovation Thérapeutique Villejuif94800 France The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette91190 France The Department of Radiology and Nuclear Medicine Radboud University Medical Center Nijmegen6525 GA Netherlands The School of Automation Nanjing University of Information Science and Technology Nanjing210044 China The School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom The Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital United States Harvard Medical School Boston United States The King’s College London United Kingdom The Tel Aviv University The Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology Hubei Wuhan430074 China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Sci

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a wide range of clinically relevant tasks. This limits the development of registration methods, the adoption of research advances into practice, and a fair benchmark across competing approaches. The Learn2Reg challenge addresses these limitations by providing a multi-task medical image registration data set for comprehensive characterisation of deformable registration algorithms. A continuous evaluation will be possible at https://***. Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation. We established an easily accessible framework for training and validation of 3D registration methods, which enabled the compilation of results of over 65 individual method submissions from more than 20 unique teams. We used a complementary set of metrics, including robustness, accuracy, plausibility, and runtime, enabling unique insight into the current state-of-the-art of medical image registration. This paper describes datasets, tasks, evaluation methods and results of the challenge, as well as results of further analysis of transferability to new datasets, the importance of label supervision, and resulting bias. While no single approach worked best across all tasks, many methodological aspects could be identified that push the performance of medical image registration to new state-of-the-art performance. Furthermore, we demystified the common belief that conventional registration methods have to be much slower than deep-learning-based methods. © 2021, CC BY.

关键词： Image registration

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Author Correction: Generation of accurate, expandable phylogenomic trees with uDance

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Nature biotechnology 2024年第5期42卷 814页

作者： Metin Balaban Yueyu Jiang Qiyun Zhu Daniel McDonald Rob Knight Siavash Mirarab Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA. Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA. Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA. School of Life Sciences Arizona State University Tempe AZ USA. Department of Pediatrics University of California San Diego La Jolla CA USA. Department of Computer Science and Engineering Jacobs School of Engineering University of California San Diego La Jolla CA USA. Department of Bioengineering University of California San Diego La Jolla CA USA. Center for Microbiome Innovation Jacobs School of Engineering University of California San Diego La Jolla CA USA. Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA. smirarab@ucsd.edu. Department of Computer Science and Engineering Jacobs School of Engineering University of California San Diego La Jolla CA USA. smirarab@ucsd.edu. Center for Microbiome Innovation Jacobs School of Engineering University of California San Diego La Jolla CA USA. smirarab@ucsd.edu.

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Retraction: LUC Algorithm in Visual Cryptography (J. Phys.: Conf. Ser. 1114 012090)

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Ratnadewi Christian Dio Alpha G Darmawan Napitupulu Heri Nurdiyanto Nuning Kurniasih Abdurrozaq Hasibuan GS Achmad Daengs Rosida Tiurma Manurung Indrya Mulyaningsih Robbi Rahim Castaka Agus Sugianto Dahlan Abdullah Department of Electrical Engineering Universitas Kristen Maranatha Bandung Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Banten Indonesia STMIK Dharma Wacana Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Universitas Islam Sumatera Utara Indonesia University of 45 Surabaya Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Bandung Indonesia Department of Education Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Politeknik TEDC Bandung Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia

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LUC Algorithm in Visual Cryptography

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Journal of Physics: Conference Series 2018年第1期1114卷

Nowadays, messaging technology in digital data form more often used and not less messages that confidentially wanted. Then it should be modified so that can be understood only by the sender and the intended recipients. All of this system can be realization by using cryptography. LUC algorithms are introduced by Smith and Lennon in 1993. LUC algorithm is an algorithm that based on the use of Lucas sequence (specific arithmetic operations derived from Lucas row) that rarely used to enhance the security of the messages. In this research, LUC algorithm is combined with visual cryptography to process the encryption and the description of a colored image. Four different images were used in the trial here. The performance of the system is assessed using Structural similarity (SSIM) which has an assessment similar to human eye. If the image quality is the same as the original image, then the SSIM value is one. Whereas if the quality of decryption image is very different from the original image then the value of SSIM is zero.

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Expression of concern: Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy

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Nanoscale 2024年第9期16卷 4919页

作者： Michael A Casasanta G M Jonaid Liam Kaylor William Y Luqiu Maria J Solares Mariah L Schroen William J Dearnaley Jarad Wilson Madeline J Dukes Deborah F Kelly Department of Biomedical Engineering Pennsylvania State University University Park PA 16802 USA. Debkelly@psu.edu. Materials Research Institute Pennsylvania State University University Park PA 16802 USA. Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Department of Electrical and Computer Engineering Duke University Durham NC 27708 USA. RayBiotech Life Peachtree Corners GA 30092 USA. Applications Science Protochips Inc. Morrisville NC 27560 USA.

Expression of concern for 'Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy' by Michael A. Casasanta , , 2021, , 7285-7293, https://***/10.1039/D1NR00388G.

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Designing the Application of Security Text Messages Into Audio Files Using Data Encryption Standard (DES) Algorithms Using the End Of File (EOF) Method

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Journal of Physics: Conference Series 2019年第1期1363卷

作者： A M H Pardede Anggi Pramana Muhammad Zarlis Akbar Iskandar Rosida Tiurma Manurung S Sriadhi Citra Kurniawan Abdurrozzaq Hasibuan Nurintan Asyiah Siregar Ayu Esteka Sari Indrya Mulyaningsih Teguh Hidayat Iskandar Alam Ibrahim Tri Listyorini Edy Winarno Tulus STMIK Kaputama Binjai Sumatera Utara Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Indonesian Language Teaching Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia Department of Informatics Engineering Universitas Muhammadiyah Sorong Sorong Indonesia Department of English Education Universitas Muhammadiyah Sorong Sorong Indonesia Department of Informatics Universitas Muria Kudus Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia

There are several ways to deal with security issues of confidential data sent via the internet, including using cryptographic techniques and steganography. Steganography is the science and art of concealing information / messages in a media in such a way that its existence is not detected by other parties who are not entitled to the information. Instead, cryptography disguises the meaning of a message, but does not hide that there is a message because the file looks suspicious. The Steganography technique used here was End Of File (EOF). The EOF technique described how to add data or files at the end of the image file. For this technique, the size of data or files that will be hidden could be larger than the size of the image file. The hidden data will be inserted at the end of the file so that it will not affect the image. This steganography application is also equipped with a cryptographic function Data Encryption Standard (DES) at the time of insertion of data that functions as a generator code and encrypts data, so that the security of a data in the file is more protected and protected from those who are not entitled to know the data.

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