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Generative AI, IoT, and blockchain in healthcare: application, issues, and solutions

Discover Internet of Things 2025年第1期5卷 1-23页

作者： Mazhar, Tehseen khan, Sunawar Shahzad, Tariq khan, Muhammad Amir Saeed, Mamoon M. Awotunde, Joseph Bamidele Hamam, Habib School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Department of Computer Science International Islamic University Islamabad44000 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Sana’a Yemen Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Science and Information Technology School Education Department Government of Punjab 31200 Layyah Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa Av. Grandes Ecoles LibrevilleBP 1989 Gabon Bridges for Academic Excellence Spectrum Tunis Tunisia

This article discusses Blockchain and Generative AI in healthcare, including their uses, difficulties, and solutions. Blockchain technology improves EHR security, privacy, and interoperability, while smart contracts streamline supply chain management and administrative procedures. Blockchain verifies and secures IoT data, improving medical care and treatment, according to case studies. Generative AI systems like ChatGPT have transformed healthcare by personalizing therapy, diagnostics, and predictive analytics. AI systems can examine massive databases to diagnose diseases early, anticipate dangers, and personalize therapies. By providing timely information, boosting treatment adherence, and giving continuous support, AI-powered virtual health assistants have enhanced patient involvement. Generative AI has additionally enhanced medical research and drug development, cutting the time and expense of introducing new medicines. Generative AI and Blockchain provide safe patient data storage, high-quality AI training datasets, and efficient healthcare operations. Scalability, energy usage, and interoperability issues remain. Scalable Blockchain designs and standardized data integration and exchange protocols are suggested by this study. These technologies could improve medical research and therapy by making them safer, more effective, and more individualized. © The Author(s) 2025.

关键词： Electronic health record

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Deep Learning-Based Decision-Making of Autonomous Vehicles to Predict Accidents

Deep Learning-Based Decision-Making of Autonomous Vehicles t...

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2023 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Khanum, Abida Lee, Chao-Yang Yang, Chu-Sing National Cheng Kung University No.1 Department of Electrical Engineering Tainan City701 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering National Formosa University Yunlin Taiwan

ISBN: (纸本)9798350313154

The autonomous vehicle system ensures safe driving by certainly controlling a vehicle's motion in the lane to reduce the risk of a collision. The proposed architecture is based on convolutional neural network (CNN) deep learning-based with three convolutional blocks. As output, the CNN framework can predict three different risk factor evaluations, i.e., high risk, medium risk, and low risk, used to predict the accident of the AV. The deep learning-based network had a better accuracy rate and computing time for all MTs with a 70% accuracy rate and an 8-ms computing time for risk prediction in autonomous vehicles. The experimental accuracy demonstrates that our trained method has fruitfully accurate results. The self-driving vehicle model successfully predicts the accident risk during driving a vehicle on the road. © 2023 IEEE.

关键词： Decision making

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ReviewRanker: A Semi-supervised Learning-Based Approach for Code Review Quality Estimation 6th

ReviewRanker: A Semi-supervised Learning-Based Approach for ...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Mahbub, Saifullah Easin Arafat, Md. Rahman, Chowdhury Rafeed Ferdows, Zannatul Hasan, Masum Department of Computer Science and Engineering United International University United City Madani Avenue Dhaka1212 Bangladesh Data Science and Engineering Department Faculty of Informatics Eötvös Loránd University Pázmány Péter Str. 1/A Budapest1117 Hungary Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka1000 Bangladesh School of Computing National University of Singapore Singapore Singapore Department of Computer Science University of Rochester RochesterNY United States

ISBN: (纸本)9789819734412

Code review is considered a key process in the software industry for minimizing bugs and improving code quality. Inspection of review process effectiveness and continuous improvement can boost development productivity. Such inspection is a time-consuming and human-bias-prone task. We propose a semi-supervised learning-based system ReviewRanker which is aimed at assigning each code review a confidence score which is expected to resonate with the quality of the review. Our proposed method is trained based on simple and well-defined labels provided by developers. The labeling task requires little to no effort from the developers and has an indirect relation to the end goal (assignment of review confidence score). ReviewRanker is expected to improve industry-wide code review quality inspection by reducing human bias and the effort required for such a task. The system has the potential of minimizing the back-and-forth cycle existing in the development and review process. Usable code and dataset for this research can be found at: https://***/saifarnab/code_review. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Self-supervised learning

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Distributed Information Bottleneck for a Primitive Gaussian Diamond MIMO Channel

Distributed Information Bottleneck for a Primitive Gaussian ...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Song, Yi Xu, Hao Wong, Kai-Kit Caire, Giuseppe Shamai Shitz, Shlomo Technical University of Berlin Faculty of Electrical Engineering and Computer Science Berlin10587 Germany University College London Department of Electronic and Electrical Engineering LondonWC1E7JE United Kingdom Technion-Israel Institute of Technology Department of Electrical and Computer Engineering Haifa3200003 Israel

ISBN: (纸本)9781665475549

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and MIMO Rayleigh fading. The channel state is an independent and identically distributed (i.i.d.) process known at the relays but unknown to the destination. The relays are oblivious, i.e., they are unaware of the codebook and treat the transmitted signal as a random process with known statistics. The bottleneck constraints prevent the relays to communicate the channel state information (CSI) perfectly to the destination. To evaluate the bottleneck rate, we provide an upper bound by assuming that the destination node knows the CSI and the relays can cooperate with each other, and also two achievable schemes with simple symbol-by-symbol relay processing and compression. Numerical results show that the lower bounds obtained by the proposed achievable schemes can come close to the upper bound on a wide range of relevant system parameters. © 2023 IEEE.

关键词： Channel state information

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Automatic Approach for Building Dataset of Citation Functions for COVID-19 Academic Papers 16

Automatic Approach for Building Dataset of Citation Function...

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16th Linguistic Annotation Workshop, LAW 2022

作者： Basuki, Setio Tsuchiya, Masatoshi Department of Computer Science and Engineering Toyohashi University of Technology 1-1 Hibarigaoka Tempaku-cho Aichi Toyohashi441-8580 Japan

ISBN: (纸本)9782493814081

This paper develops a new dataset of citation functions of COVID-19-related academic papers. Because the preparation of new labels of citation functions and building a new dataset requires much human effort and is time-consuming, this paper uses our previous citation functions that were built for the computer Science (CS) domain, which consists of five coarse-grained labels and 21 fine-grained labels. This paper uses the COVID-19 Open Research Dataset (CORD-19) and extracts 99.6k random citing sentences from 10.1k papers. These citing sentences are categorized using the classification models built from the CS domain. The manually check on 475 random samples resulted accuracies of 76.6% and 70.2% on coarse-grained labels and fine-grained labels, respectively. The evaluation reveals three findings. First, two fine-grained labels experienced meaning shift while retaining the same idea. Second, the COVID-19 domain is dominated by statements highlighting the importance, cruciality, usefulness, benefit, consideration, etc. of certain topics for making sensible argumentation. Third, discussing State of The Arts (SOTA) in terms of their outperforming previous works in the COVID-19 domain is less popular compared to the CS domain. Our results will be used for further dataset development by classifying citing sentences in all papers from CORD-19. © 2022 European Language Resources Association (ELRA).

关键词： COVID-19

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Deep Reinforcement Learning-Based Robust Design for an IRS-Assisted MISO-NOMA System

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 424-441页

作者： Waraiet, Abdulhamed Cumanan, Kanapathippillai Ding, Zhiguo Dobre, Octavia A. University of York School of Physics Engineering and Technology YorkYO10 5DD United Kingdom Khalifa University Department of Computer and Communication Engineering Abu Dhabi United Arab Emirates Memorial University Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada

In this paper, we propose a robust design for an intelligent reflecting surface (IRS)-assisted multiple-input single output non-orthogonal multiple access (NOMA) system. By considering channel uncertainties, the original robust design problem is formulated as a sum-rate maximization problem under a set of constraints. In particular, the uncertainties associated with reflected channels through IRS elements and direct channels are taken into account in the design and they are modelled as bounded errors. However, the original robust problem is not jointly convex in terms of beamformers at the base station and phase shifts of IRS elements. Therefore, we reformulate the original robust design as a reinforcement learning problem and develop an algorithm based on the twin-delayed deep deterministic policy gradient agent (also known as TD3). In particular, the proposed algorithm solves the original problem by jointly designing the beamformers and the phase shifts, which is not possible with conventional optimization techniques. Numerical results are provided to validate the effectiveness and evaluate the performance of the proposed robust design. In particular, the results demonstrate the competitive and promising capabilities of the proposed robust algorithm, which achieves significant gains in terms of robustness and system sum-rates over the baseline deep deterministic policy gradient agent. In addition, the algorithm has the ability to deal with fixed and dynamic channels, which gives deep reinforcement learning methods an edge over hand-crafted convex optimization-based algorithms. © 2023 CCBY.

关键词： Heuristic algorithms

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Insurance Plan for Service Assurance in Cloud Computing Market with Incomplete Information

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Journal of Communications and Information Networks 2022年第1期7卷 11-22页

作者： Yanru Zhang Chunxiao Jiang Nguyen H.Tran Shengrong Bu FeiRichard Yu Zhu Han College of Computer Science and Engineering the University of Electronic Science and Technology of ChinaChengdu 611731China Shenzhen Institute for Advanced Study UESTCLonghuaShenzhen 518110China Tsinghua Space Center Tsinghua UniversityBeijing 10084China School of Computer Science the University of SydneySydneyNew South WalesAustralia Department of Engineering Brock UniversityONCanada School of Information Technology Depart.of Systems and Computer EngineeringCarleton UniversityOttawa K1S 5B6ONCanada Department of Electrical and Computer Engineering the University of HoustonHouston 77004TXUSA

Nowadays,cloud computing has been identified as new opportunities for migrating to the expected agility,reuse,and adaptive capabilities that can support the ever changing IT trends and ***,the rapid evolution of those technologies also comes with open issues such as security,privacy,integrity,quality of services,and their possible detrimental *** this work,the concept of insurance is introduced to compensate the cloud computing customers when encountering those failures if service providers(SPs)have insurance ***,we consider the situation when the insurer is unable to see the system failure risk levels of the SPs,which is usually seen as an incomplete information market,in contrast with the optimal situation in a complete information ***,an insurance-based cloud computing architecture is proposed to build a monetary credit system in which the cloud computing SP pays a premium for a certain coverage to the ***,problem is formulated to solve the optimal insurance plan in complete and incomplete information markets,together with detail analysis of insurance policies in both cases are ***,simulation results show the properties of the two insurance plans and parameters that affect the design of the insurance plan.

关键词： service assurance cloud computing market incomplete information game theory insurance plan

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One-shot functional photoacoustic microscopy for monitoring traumatic brain injury 16

One-shot functional photoacoustic microscopy for monitoring ...

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16th International Conference on Photonics and Imaging in Biology and Medicine, PIBM 2023

作者： Zhang, Yameng Chen, Yang Qi, Xinping Li, Weitao Department of Computer Engineering Nanjing Institute of Technology No.1 Hongjing Avenue Nanjing Jiangsu211167 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu211106 China

ISBN: (纸本)9781510667341

Photoacoustic microscopy (PAM) is a novel medical imaging technique developed rapidly in recent years with the advantages of high resolution, high contrast, and no ionizing radiation. In this study, we developed a one-shot functional photoacoustic microscopy (OS-fPAM) system for assessing traumatic brain injury (TBI). The OS-fPAM system only employed a single 532 nm nanosecond pulse laser with Raman delay optical path control, which can produce both 532 nm and 553 nm laser beams. The dual-wavelength beams were then coupled via a dichroic mirror and focused on the surface of the experimental sample. Then, the photoacoustic signal was collected and amplified in the ultrasonic signal acquisition module, and the blood oxygen saturation (sO2) image was calculated by two wavelength photoacoustic images. The feasibility of the OS-fPAM system was performed through the calibration experiments with different ratios of red ink and blue ink. Meanwhile, the OS-fPAM system can monitor microvascular structures and sO2 in the TBI model on mice for 96 hours in vivo with a spatial resolution of ∼40 μm, demonstrating the potential to evaluate rehabilitation and cerebral vascular damage. © 2023 SPIE.

关键词： Photoacoustic microscopy

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An Hybrid Combination of Ontology Along with RDF technology for ICU Systems Through CBM 4

An Hybrid Combination of Ontology Along with RDF Technology ...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Nikshya, J.Ebens Sanmugavalli, P. Jayachitra, S. Kaur, Manjeet Jalal, Sarah Salah Hussain, Ahmed Scad College of Engineering and Technology Department of Ece Tamilnadu Tirunelveli India M.Kumarasamy College of Engineering Department of Ece Karur India Psna College of Engineering and Technology Department of Ece Dindigul India Govt.P.G.College Department of Computer Science and Applications Sector 1 Panchkula Haryana Panchkula India National University of Science and Technology Collage of Nursing Dhi Qar64001 Iraq Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9798350360165

Modern data generation poses distinct issues due to its enormous volume, quick speed, and wide variation, necessitating the use of specialised tools and techniques for analysis and inference. These issues are never more evident than in the healthcare industry, where computerised patient records and biological research create data at an exponential rate. Furthermore, it is now essential to analyse data from all areas that have an influence on patient health, including medical and oral diseases, given the increased emphasis on holistic treatment. There are interdependencies among many medical and dental disorders, necessitating coordinated care. However, technological obstacles including different formats for data collection and storage, restricted patient information exchange, and insufficient decision support tools have made collaborative patient care extremely difficult. In response to these challenges, this work explores the development and application of ontology and resource description framework (RFD) rules to construct an evidence-based, reusable, cross-domain knowledge base. In a sample application of this knowledge base, the effectiveness of the technique for reasoning and decision assistance in a range of patient information domains is assessed using Protégé. © 2024 IEEE.

关键词： Electronic health record

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Performance Evaluation of Three-Dimensional UWB Real-Time Locating Auto-Positioning System for Fire Rescue

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Intelligent Automation & Soft Computing 2023年第9期37卷 3039-3058页

作者： Hang Yang Xunbo Li Witold Pedrycz School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu611731China Department of Electrical and Computer Engineering University of AlbertaEdmontonT6G 1H9Canada School of Information Engineering Southwest University of Science and TechnologyMianyang621000China

Fire rescue challenges and solutions have evolved from straightfor-ward plane rescue to encompass 3D space due to the rise of high-rise city ***,this study facilitates a system with quick and simplified on-site launching and generates real-time location data,enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise ***-positioning with step-by-step instructions is proposed when launching the locating system,while no extra measuring instrument like Total Station(TS)is ***-time location tracking is provided via a 3D space real-time locating system(RTLS)constructed using Ultra-wide Bandwidth technology(UWB),which requires electromagnetic waves to pass through concrete walls.A hybrid weighted least squares with a time difference of arrival(WLS/TDOA)positioning method is proposed to address real path-tracking issues in 3D space and to meet RTLS requirements for quick computing in real-world *** 3D WLS/TDOA algorithm is theoretically constructed with the Cramer-Rao lower bound(CRLB).The computing complexity is reduced to the lower bound for embedded hardware to directly compute the time differential of the arriving signals using the time-to-digital converter(TDC).The results of the experiments show that the errors are controlled when the positioning algorithm is applied in various complicated situations to fulfill the requirements of engineering *** statistical analysis of the data reveals that the proposed UWB RTLS auto-positioning system can track target tags with an accuracy of 0.20 m.

关键词： 3D space positioning ultra-wideband real-time locating system time difference of arrival Cramer-Rao lower bound fire rescue

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