检索结果-内蒙古大学图书馆

Agriculture Spatiotemporal Business Intelligence using Open Data Integration

学校读者我要写书评

暂无评论

Agriculture Spatiotemporal Business Intelligence using Open ...

International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Irya Wisnubhadra Stephanie Pamela Adithama Safiza Suhana Kamal Baharin Nanna Suryana Herman Informatics Engineering Department Atma Jaya Yogyakarta University Yogyakarta Indonesia Centre for Advanced Computing Technology Faculty of Information and Communication Technology Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (数字)9781728145204

ISBN: (纸本)9781728145211

Business Intelligence is a technology for collecting, transforming, and presenting data for analysis as a tool for supporting decision making. Business Intelligence using Data Warehouse, Multidimensional data, and Online Analytical Processing (OLAP) has proven to be useful for obtaining information and knowledge relevant to the business. Nowadays the development of the internet with Web 2.0 model is increasing the availability of data over the internet. Linked Open Data (LOD), Open Data, and Open Government Data is constantly growing, producing a large amount of valuable data in the form of semi-structured data, flexible and machine-readable. Data sharing on agricultural production is one of the requirements for the best of analysis of agricultural production, but most of the data is still in the format of 2/3-stars open data and does not yet have spatial data that facilitates analysis based on spatial dimensions. The emerging open data concept makes the data warehouse more dynamic and can accommodate external data. Spatiotemporal support in open data also enables a more sophisticated analysis of data with spatial queries. This research develops tools to integrate agricultural data originating from the Village and Rural Area Information Systems (SIDeKa) that has open distributed data, a service-oriented approach, and spatiotemporal data. This paper also describes the design of business intelligence and multidimensional data for analysis and decision-making tools that enable spatiotemporal and non-spatial based analysis. This paper also highlights the opportunities for scaling and sustaining the initiative.

关键词： Tools Government Agriculture Business intelligence Spatiotemporal phenomena Data warehouses

Why is the Winner the Best?

学校读者我要写书评

暂无评论

Why is the Winner the Best?

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

关键词：

Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within Generative AI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023, CC0.

关键词： Machine learning

A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

学校读者我要写书评

暂无评论

arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

Corrigendum to “Hybridizing flower pollination algorithm with particle swarm optimization for enhancing the performance of IPv6 intrusion detection system” [Alex. Eng. J. 104 (2024) 504–514]

学校读者我要写书评

暂无评论

Alexandria engineering Journal 2025年 110卷 376-376页

作者： Adnan Hasan Bdair AIghuraibawi Selvakumar Manickam Zaid Abdi Alkareem Alyasseri Rosni Abdullah Ayman Khallel Riyadh Rahef Nuiaa Al Ogaili Fahd N. Al-Wesabi Abdulsamad Ebrahim Yahya National Advanced IPv6 Centre (NAv6) Universiti Sains Malaysia Penang 11800 Malaysia Baghdad College of Economic Sciences University Baghdad Iraq Information Technology Research and Development Center University of Kufa Najaf Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq School of Computer Sciences Universiti Sains Malays Penang 11800 Malaysia Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Malaysia Department of Cybersecurity Engineering Technology Al Hikma University College Baghdad Iraq Department of Computer Science/ College of Computer Science and Information Technology Wasit University Kut Wasit 52001 Iraq Department of Computer Science College of Science & Art at Mahayil King Khalid University Saudi Arabia Department of Information Technology College of Computing and Information Technology Northern Border University Arar Saudi Arabia

Single-Shot Secure Quantum Network Coding for General Multiple Unicast Network with Free One-Way Public Communication

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Kato, Go Owari, Masaki Hayashi, Masahito NTT Communication Science Laboratories NTT Corporation Japan Department of Computer Science Faculty of Informatics Shizuoka University Japan Graduate School of Mathematics Nagoya University Japan Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China Quantum Computing Peng Cheng Laboratory Shenzhen518000 China Centre for Quantum Technologies National University of Singapore Singapore

It is natural in a quantum network system that multiple users intend to send their quantum message to their respective receivers, which is called a multiple unicast quantum network. We propose a canonical method to derive a secure quantum network code over a multiple unicast quantum network from a secure classical network code. Our code correctly transmits quantum states when there is no attack. It also guarantees the secrecy of the transmitted quantum state even with the existence of an attack when the attack satisfies a certain natural condition. In our security proof, the eavesdropper is allowed to modify wiretapped information dependently on the previously wiretapped messages. Our protocol guarantees the secrecy by utilizing one-way classical information transmission (public communication) in the same direction as the quantum network although the verification of quantum information transmission requires two-way classical communication. Our secure network code can be applied to several networks including the butterfly network. Copyright © 2020, The Authors. All rights reserved.

关键词： Network coding

Optimizing a parameterized controlled gate with Free Quaternion Selection

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Kurogi, Hiroyoshi Endo, Katsuhiro Sato, Yuki Sugawara, Michihiko Wada, Kaito Sugisaki, Kenji Kanno, Shu Watanabe, Hiroshi C. Nakano, Haruyuki Department of Chemistry Graduate School of Science Kyushu University 744 Motooka Nishi-ku Fukuoka819-0395 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan 1-1-1 Umezono Ibaraki Tsukuba305-8568 Japan Toyota Central R & D Labs. Inc. Koraku Mori Building 10F 1-4-14 Koraku Bunkyo-ku Tokyo112-0004 Japan Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku-ku Yokohama223-8522 Japan Graduate School of Science and Technology Keio University 7-1 Shinkawasaki Saiwai-ku Kawasaki212-0032 Japan Keio University 2-15-45 Mita Minato-ku Tokyo108-8345 Japan Centre for Quantum Engineering Research and Education TCG Centres for Research and Education in Science and Technology Salt Lake Sector V Kolkata700091 India Mitsubishi Chemical Corporation Science & Innovation Center Yokohama227-8502 Japan Department of Chemistry Faculty of Science Kyushu University 744 Motooka Nishi-ku Fukuoka819-0395 Japan

In variational algorithms, quantum circuits are conventionally parametrized with respect to single-qubit gates. In this study, we parameterize a generalized controlled gate and propose an algorithm to estimate the optimal parameters for locally minimizing the cost value, where we extend the free quaternion selection method, an optimization method for a single-qubit gate. To benchmark the performance, we apply the proposed method to various optimization problems, including the Variational Quantum Eigensolver (VQE) for Ising and molecular Hamiltonians, Variational Quantum Algorithms (VQA) for fidelity maximization, and unitary compilation of time evolution operators. In these applications, the proposed method shows efficient optimization and greater expressibility with shallower circuits than other methods. Furthermore, this method is also capable of generalizing and fully optimizing particle-number-conserving gates, which are in demand in chemical systems applications. Taking advantage of this property, we have actually approximated time evolution operators of molecular Hamiltonian and simulated the dynamics with shallower circuits in comparison to the standard implementation by Trotter decomposition. © 2024, CC BY-NC-SA.

关键词： Hamiltonians

Referral for disease-related visual impairment using retinal photograph-based deep learning: a proof-of-concept, model development study

学校读者我要写书评

暂无评论

The Lancet Digital Health 2021年第1期3卷 e29-e40页

作者： Tham, Yih-Chung Anees, Ayesha Zhang, Liang Goh, Jocelyn Hui Lin Rim, Tyler Hyungtaek Nusinovici, Simon Hamzah, Haslina Chee, Miao-Li Tjio, Gabriel Li, Shaohua Xu, Xinxing Goh, Rick Tang, Fangyao Cheung, Carol Yim-Lui Wang, Ya Xing Nangia, Vinay Jonas, Jost B Gopinath, Bamini Mitchell, Paul Husain, Rahat Lamoureux, Ecosse Sabanayagam, Charumathi Wang, Jie Jin Aung, Tin Liu, Yong Wong, Tien Yin Cheng, Ching-Yu Singapore Eye Research Institute Singapore National Eye Centre Singapore Duke-NUS Medical School Singapore Institute of High Performance Computing A*STAR Singapore School of Chemical and Biomedical Engineering Division of Bioengineering Nanyang Technological University Singapore Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region Hong Kong Beijing Institute of Ophthalmology Beijing Ophthalmology and Visual Science Key Lab Beijing Tongren Eye Center Beijing Tongren Hospital Capital Medical University Beijing China Suraj Eye Institute Nagpur India Department of Ophthalmology Medical Faculty Mannheim of the Ruprecht-Karis-University Heidelberg Mannheim Germany Centre for Vision Research Department of Ophthalmology The Westmead Institute for Medical Research The University of Sydney Westmead Hospital Westmead NSW Australia Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore

Background: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to eye diseases. The emergence of deep learning technology offers new opportunities to revolutionise this clinical referral pathway. We aimed to assess the performance of a newly developed deep learning algorithm for detection of disease-related visual impairment. Methods: In this proof-of-concept study, using retinal fundus images from 15 175 eyes with complete data related to best-corrected visual acuity or pinhole visual acuity from the Singapore Epidemiology of Eye Diseases Study, we first developed a single-modality deep learning algorithm based on retinal photographs alone for detection of any disease-related visual impairment (defined as eyes from patients with major eye diseases and best-corrected visual acuity of <20/40), and moderate or worse disease-related visual impairment (eyes with disease and best-corrected visual acuity of <20/60). After development of the algorithm, we tested it internally, using a new set of 3803 eyes from the Singapore Epidemiology of Eye Diseases Study. We then tested it externally using three population-based studies (the Beijing Eye study [6239 eyes], Central India Eye and Medical study [6526 eyes], and Blue Mountains Eye Study [2002 eyes]), and two clinical studies (the Chinese University of Hong Kong's Sight Threatening Diabetic Retinopathy study [971 eyes] and the Outram Polyclinic Study [1225 eyes]). The algorithm's performance in each dataset was assessed on the basis of the area under the receiver operating characteristic curve (AUC). Findings: In the internal test dataset, the AUC for detection of any disease-related visual impairment was 94·2% (95% CI 93·0–95·3;sensitivity 90·7% [87·0–93·6];specificity 86·8% [85·6–87·9]). The AUC for moderate or worse disease-related visual impairment was 93·9% (95% CI 92·2–95

关键词：

Screening and evaluation of potential clinically significant HIV drug combinations against SARS-CoV-2 virus

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Tomić, Draško Skala, Karolj Szasz, Attila Marcel Rezeli, Melinda Vrca, Vesna Bačić Pirkić, Boris Petrik, Jozsef Janđel, Vladimir Periša, Marija Milković Rogina, Branka Medved Mesarić, Josip Davidović, Davor Lipić, Tomislav Center for Informatics and Computing Ruđer Bošković Institute Zagreb Croatia Department of Bioinformatics and Cancer Center Semmelweis University Budapest Hungary Department of Biomedical Engineering Lund University Lund Sweden Central Hospital Pharmacy Clinical Hospital Center Dubrava Zagreb Croatia Surgery Orthopedics and Ophthalmology Clinic Faculty of Veterinary Medicine University of Zagreb Zagreb Croatia Department of Medical Biochemistry and Hematology Faculty of Pharmacy and Biochemistry University of Zagreb Zagreb Croatia Deprtment of Obstetricy Clinical Hospital Centre Zagreb Croatia Institute of Pathology School of Medicine University of Zagreb Zagreb Croatia Laboratory for Information and Signal Processing Division of Electronics Ruđer Bosković Institute Zagreb Croatia Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

In this study, we investigated the inhibition of SARS-CoV-2 spike glycoprotein with HIV drugs and their combinations. This glycoprotein is essential for the reproduction of the SARS-COV-2 virus, so its inhibition opens new avenues for the treatment of patients with COVID-19 disease. In doing so, we used the VINI in silico model of cancer, whose high accuracy in finding effective drugs and their combinations was confirmed in vitro by comparison with existing results from NCI-60 bases, and in vivo by comparison with existing clinical trial results. In the first step, the VINI model calculated the inhibition efficiency of SARS-CoV-2 spike glycoprotein with 44 FDA-approved antiviral drugs. Of these drugs, HIV drugs have been shown to be effective, while others mainly have shown weak or no efficiency. Subsequently, the VINI model calculated the inhibition efficiency of all possible double and triple HIV drug combinations, and among them identified ten with the highest inhibition efficiency. These ten combinations were analyzed by Medscape drug-drug interaction software and LexiComp Drug Interactions. All combinations except the combination of cobicistat_abacavir_rilpivirine appear to have serious interactions (risk rating category D) when dosage adjustments/reductions are required for possible toxicity. Finally, the VINI model compared the inhibition efficiency of cobicistat_abacivir_rilpivirine combination with cocktails and individual drugs already used or planned to be tested against SARS-CoV-2. Combination cobicistat_abacivir_rilpivirine demonstrated the highest inhibition of SARS-CoV-2 spike glycoprotein over others. Thus, this combination seems to be a promising candidate for the further in vitro testing and clinical trials. Copyright © 2020, The Authors. All rights reserved.

关键词： SARS