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Clinical Information Systems and Artificial Intelligence: Recent Research Trends

Carlo Combi, Giuseppe Pozzi
2019 IMIA Yearbook of Medical Informatics  
Results: We defined a taxonomy of major features and research areas of CIS, HIS, EHR systems. We also defined a taxonomy for the use of Artificial Intelligence (AI) techniques on healthcare data.  ...  In the light of these taxonomies, we report on the most relevant papers from the literature.  ...  Acknowledgements This work has been partially funded by the University of Verona, within 2017-2019 RIBA project "Extending OLAP data analysis with temporal and statistical operators and its application  ... 
doi:10.1055/s-0039-1677915 pmid:31419820 pmcid:PMC6697548 fatcat:sp2t45gr2fauhg5tzwq3c2izki

Deep Learning for Information Systems Research [article]

Sagar Samtani, Hongyi Zhu, Balaji Padmanabhan, Yidong Chai, Hsinchun Chen
2020 arXiv   pre-print
First, we systematically summarize the major components of DL in a novel Deep Learning for Information Systems Research (DL-ISR) schematic that illustrates how technical DL processes are driven by key  ...  Taken together, these contributions provide IS scholars a timely framework to advance the scale, scope, and impact of deep learning research.  ...  APPENDIX A: SUMMARY OF DEEP LEARNING PAPERS PUBLISHED IN PREVAILING INFORMATION SYSTEMS VENUES We reviewed all deep learning papers published in prevailing IS journals over the past five years (2016)  ... 
arXiv:2010.05774v1 fatcat:y2mj5m7qaremrf6jvryhxk6vgq

6G Wireless Systems: A Vision, Architectural Elements, and Future Directions

Latif U. Khan, Ibrar Yaqoob, Muhammad Imran, Zhu Han, Choong Seon Hong
2020 IEEE Access  
We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies.  ...  We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledgerbased authentication  ...  The authors in [26] focused on 6G use cases, enabling technologies, and open research challenges.  ... 
doi:10.1109/access.2020.3015289 fatcat:x5bpksqgezgg7jylzmvlipcde4

Reinforcement Learning for Intelligent Healthcare Systems: A Comprehensive Survey [article]

Alaa Awad Abdellatif, Naram Mhaisen, Zina Chkirbene, Amr Mohamed, Aiman Erbad, Mohsen Guizani
2021 arXiv   pre-print
After that, we provide a deep literature review for the applications of RL in I-health systems.  ...  Finally, we highlight emerging challenges and outline future research directions in driving the future success of RL in I-health systems, which opens the door for exploring some interesting and unsolved  ...  ACKNOWLEDGMENT This work was made possible by NPRP grant # NPRP12S-0305-190231 from the Qatar National Research Fund (a member of Qatar Foundation).  ... 
arXiv:2108.04087v1 fatcat:ifdpiqwunrawbmpfy6ftjk43g4

Cyber-Physical-Social Systems: Taxonomy, Challenges, and Opportunities

Shabnam Pasandideh, Pedro Pereira, Luis Gomes
2022 IEEE Access  
In this study, we provide a systematic review of the definition of CPSS and propose a taxonomy to define CPSS more constructively.  ...  Finally, the issues and opportunities in CPSSs are described.  ...  ACKNOWLEDGMENT This work was partially financed by the Portuguese Agency "Fundação para a Ciência e a Tecnologia" (FCT), under the framework of project UID/EEA/00066/2020.  ... 
doi:10.1109/access.2022.3167441 fatcat:yfwn54bgpjba7ddmsfuwefpula

Securing AI-based Healthcare Systems using Blockchain Technology: A State-of-the-Art Systematic Literature Review and Future Research Directions [article]

Rucha Shinde, Shruti Patil, Ketan Kotecha, Vidyasagar Potdar, Ganeshsree Selvachandran, Ajith Abraham
2022 arXiv   pre-print
learning on heterogeneous medical data. 5) The issues like single point of failure, non-transparency in healthcare systems can be resolved with Blockchain.  ...  A global solution for all sort of adversarial attacks on AI based healthcare. However, this technique has significant limits and challenges that need to be addressed in future studies.  ...  In Section IV, we have provided a literature review of blockchain for AI-based healthcare considering challenges.  ... 
arXiv:2206.04793v1 fatcat:v2wrluwugja65btmjct5wlrfm4

A review on voice pathology: Taxonomy, diagnosis, medical procedures and detection techniques, open challenges, limitations, and recommendations for future directions

Nuha Qais Abdulmajeed, Belal Al-Khateeb, Mazin Abed Mohammed
2022 Journal of Intelligent Systems  
This review covered voice pathology taxonomy, detection techniques, open challenges, limitations, and recommendations for future directions to provide a clear background for doctors and patients.  ...  This study highlights the following issues: recent studies, methods of voice pathology detection, machine learning and deep learning (DL) methods used in data classification, main datasets utilized, and  ...  A comprehensive evaluation and taxonomy of the latest research and techniques have been offered in this article to leverage deep learning and IoT in a variety of healthcare applications, primarily in voice  ... 
doi:10.1515/jisys-2022-0058 fatcat:dvh3krao6nfjzengdphvrqqdia

Smart anomaly detection in sensor systems: A multi-perspective review

L. Erhan, M. Ndubuaku, M. Di Mauro, W. Song, M. Chen, G. Fortino, O. Bagdasar, A. Liotta
2020 Information Fusion  
The review points to the most promising intelligent-sensing methods, and pinpoints a set of interesting open issues and challenges.  ...  Herein, we review state-of-the-art methods that may be employed to detect anomalies in the specific area of sensor systems, which poses hard challenges in terms of information fusion, data volumes, data  ...  The review takes into account the most interesting smart sensing methods, and identifies a set of appealing open issues and challenges.  ... 
doi:10.1016/j.inffus.2020.10.001 fatcat:r65qp56ipzebnasd33o3wxkfo4

Digital Twin of Wireless Systems: Overview, Taxonomy, Challenges, and Opportunities [article]

Latif U. Khan, Zhu Han, Walid Saad, Ekram Hossain, Mohsen Guizani, Choong Seon Hong
2022 arXiv   pre-print
In this tutorial, we present a comprehensive overview on digital twins for wireless systems.  ...  Finally, open research challenges and opportunities are presented along with causes and possible solutions.  ...  We also derive a comprehensive taxonomy of digital twins-based wireless systems and presented open research challenges. C.  ... 
arXiv:2202.02559v1 fatcat:v6afo5n2srfqle3se3zbjarzeq

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review

Saima Gulzar Ahmad, Tassawar Iqbal, Anam Javaid, Ehsan Ullah Munir, Nasira Kirn, Sana Ullah Jan, Naeem Ramzan
2022 Sensors  
This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order.  ...  This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants.  ...  Acknowledgments: The authors would like to thank the anonymous reviewers for their insightful comments and suggestions on improving this paper.  ... 
doi:10.3390/s22124362 pmid:35746144 pmcid:PMC9228894 fatcat:kwep2welvndhjge5oacbcwql6q

A Survey on Session-based Recommender Systems [article]

Shoujin Wang, Longbing Cao, Yan Wang, Quan Z. Sheng, Mehmet Orgun, Defu Lian
2021 arXiv   pre-print
We propose a general problem statement of SBRSs, summarize the diversified data characteristics and challenges of SBRSs, and define a taxonomy to categorize the representative SBRS research.  ...  In recent years, session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs.  ...  Liang Hu and Mr. Yan Zhao for their constructive suggestions on this work. This work was supported by Australian Research Council Discovery Grants (DP180102378, DP190101079 and FT190100734).  ... 
arXiv:1902.04864v3 fatcat:oka5bvibzzbk5oreltrupehaey

A Comprehensive Survey on Machine Learning-Based Big Data Analytics for IoT-Enabled Smart Healthcare System

Wei Li, Yuanbo Chai, Fazlullah Khan, Syed Rooh Ullah Jan, Sahil Verma, Varun G. Menon, Kavita, Xingwang Li
2021 Journal on spesial topics in mobile networks and applications  
In this paper, we have presented a comprehensive review on the application of machine learning techniques for big data analysis in the healthcare sector.  ...  Although, big data analytics and machine learning are extensively researched, there is a lack of study that exclusively focus on the evolution of ML-based techniques for big data analysis in the IoT healthcare  ...  Also highlight the most recent advances in machine learning techniques and their diverse applications, challenges and open issues.  ... 
doi:10.1007/s11036-020-01700-6 fatcat:mky7gg34cjhatacs2vlpamh5zy

Trustworthy Intrusion Detection in E-Healthcare Systems

Faiza Akram, Dongsheng Liu, Peibiao Zhao, Natalia Kryvinska, Sidra Abbas, Muhammad Rizwan
2021 Frontiers in Public Health  
This paper proposes an approach for effective intrusion detection in the e-healthcare environment to maintain PHR in a safe IoT-net using an adaptive neuro-fuzzy inference system (ANFIS).  ...  The security of data servers in all sectors (mainly healthcare) has become one of the most crucial challenges for researchers.  ...  The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems.  ... 
doi:10.3389/fpubh.2021.788347 pmid:34926397 pmcid:PMC8678532 fatcat:4iso64ixvndtniok2igg5xapeq

Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges [article]

Huaming Chen, M. Ali Babar
2022 arXiv   pre-print
Finally, we summarise the literature for system security assurance, and motivate the future research directions with open challenges.  ...  However, how to securely develop the machine learning-based modern software systems (MLBSS) remains a big challenge, for which the insufficient consideration will largely limit its application in safety-critical  ...  While secure deep learning engineering is presented as a promising approach that leads to quality assurance of the systems, it lacks an in-depth discussion of the relevant process.  ... 
arXiv:2201.04736v1 fatcat:5g3b2mbapjgelltogqiubv5kda

Cybersecurity of Industrial Cyber-Physical Systems: A Review

Hakan Kayan, Matthew Nunes, Omer Rana, Pete Burnap, Charith Perera
2022 ACM Computing Surveys  
Hence, finding a solution for the problems mentioned in these reports is relatively hard. We bridge this gap by defining and reviewing ICPSs from a cybersecurity perspective.  ...  In particular, multi-dimensional adaptive attack taxonomy is presented and utilized for evaluating real-life ICPS cyber incidents.  ...  ACKNOWLEDGMENTS This work is partially supported by EPSRC PETRAS (EP/S035362/1) and GCHQ National Resilience Fellowship.  ... 
doi:10.1145/3510410 fatcat:fa73nli6zzfxjkedcosbj3j4li
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