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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
., edge intelligence, smart core network, and dynamic treatment regimes.  ...  Reinforcement Learning (RL) has witnessed an intrinsic breakthrough in solving a variety of complex problems for diverse applications and services.  ...  The authors in [135] develop a privacy-preserving RL-based framework for patient-centric dynamic treatment regime.  ... 
arXiv:2108.04087v1 fatcat:ifdpiqwunrawbmpfy6ftjk43g4

2021 Index IEEE Internet of Things Journal Vol. 8

2021 IEEE Internet of Things Journal  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, JIoT Feb. 1, 2021 2040-2050 An Incentive Mechanism for Privacy-Preserving Crowdsensing via Deep Reinforcement Learning.  ...  ., +, JIoT April 15, 2021 6143-6153 An Incentive Mechanism for Privacy-Preserving Crowdsensing via Deep Reinforcement Learning.  ... 
doi:10.1109/jiot.2022.3141840 fatcat:42a2qzt4jnbwxihxp6rzosha3y

Collecting, exploring and sharing personal data: Why, how and where

Vero Estrada-Galiñanes, Katarzyna Wac, Robert Hoehndorf
2019 Data Science  
However, there are no simple and reliable ways for individuals to securely collect, explore and share these sources.  ...  To this end, we present preliminary specifications of an open platform for personal data storage and quality of life research.  ...  Acknowledgements We thank Bastian Greshake Tzovaras and Mad Price Ball from Open Humans Foundation for sharing valuable insights and expertise that improved this work although they may not agree with all  ... 
doi:10.3233/ds-190025 fatcat:cfyidf3ezvac7ltmnjy36cmwmq

Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications [article]

Khaled B. Letaief, Yuanming Shi, Jianmin Lu, Jianhua Lu
2021 arXiv   pre-print
In this paper, we shall provide our vision for scalable and trustworthy edge AI systems with integrated design of wireless communication strategies and decentralized machine learning models.  ...  , and privacy leakage in both of the training and inference processes.  ...  An RL approach for decisions making in patient treatment was introduced in [317] to realize safe and risk-conscious healthcare practice.  ... 
arXiv:2111.12444v1 fatcat:crrbtfylvjeihogumggdnxcbpq

Privacy-Preserving Vehicle Assignment in the Parking Space Sharing System

Tingting Fu, Peng Liu, Kun Liu, Peng Li, Ximeng Liu
2020 Wireless Communications and Mobile Computing  
To solve this problem, we propose a new architecture for parking space sharing, integrating homomorphic cryptography into the design of a secure protocol for parking space searching and booking.  ...  The proposed privacy-preserving matching scheme (PPMS) is constructed in an untrusted third-party service system including two independent entities, namely, a server and an intermediary platform.  ...  Li proposes a privacy-preserving reinforcement learning framework for a patient-centric dynamic treatment regime [21] .  ... 
doi:10.1155/2020/8862652 fatcat:3icgr4ikkjf5dmmlrndefncjhi

Differentially Private Policy Evaluation [article]

Borja Balle, Maziar Gomrokchi, Doina Precup
2016 arXiv   pre-print
We present the first differentially private algorithms for reinforcement learning, which apply to the task of evaluating a fixed policy.  ...  We establish two approaches for achieving differential privacy, provide a theoretical analysis of the privacy and utility of the two algorithms, and show promising results on simple empirical examples.  ...  Learning in a large function space: Privacy-preserving mechanisms for svm learning. Journal of Privacy and Confidentiality, 4(1):4, 2012. Adam Smith and Abhradeep Thakurta.  ... 
arXiv:1603.02010v1 fatcat:nd552u3mdrbyriqmve52d7vb5u

A Proposed National Health Information Network Architecture and Complementary Federal Preemption of State Health Information Privacy Laws

John W. Hill, Arlen W. Langvardt, Anne P. Massey, Jonathan E. Rinehart
2011 American Business Law Journal  
NHIN architecture and patient privacy laws are interdependent, and information flow is impeded by disparate state privacy laws layered onto federal law.  ...  of e-health must be attended by appropriate protections for privacy and security of personal health information, and most states have enacted health information privacy laws. 15 Already there is evidence  ...  This study proposes a framework for NHIN construction coupled with complementary federal privacy protection regime.  ... 
doi:10.1111/j.1744-1714.2011.01120.x fatcat:xdqwqlputbgxpmepafeco4bprq

MyHealthMyData (MHMD): Deliverable 2.6 - Privacy-by-design and compliance assessment

Lorenzo Cristofaro, Rocco Panetta
2019 Zenodo  
The MHMD Privacy by design and compliance assessment describes MHMD actors with relevant roles, obligations and responsibilities, personal data categories and processing operations involved, system components  ...  It has been produced to assess and certify the compliance of the MHMD system to the data privacy and security constraints and requirements set out in the GDPR.  ...  In sum, following are the main measures that have been developed for securing the Datasets under MHMD: 1. a privacy-preserving data publication engine implementing privacy-by-design analytics and data  ... 
doi:10.5281/zenodo.3541593 fatcat:e4d4ophzavchxddosamaw3xkre

Participatory Aspects of ICT Infrastructures for Cancer Management [chapter]

Haridimos Kondylakis, Lefteris Koumakis, Ketti Mazzocco, Manolis Tsiknakis, Kostas Marias
2019 P5 eHealth: An Agenda for the Health Technologies of the Future  
, privacy-preserving data and literature mining, a key component of VPH research.  ...  The nature of malignant diseases such as cancer requires patients to learn about and comprehend the illness, make difficult decisions regarding ensuing treatment, and cope with the consequences of the  ... 
doi:10.1007/978-3-030-27994-3_6 fatcat:qgur5hwzbzcmxm4svgwcns35gm

Intelligent Software Web Agents: A Gap Analysis [article]

Sabrina Kirrane
2021 arXiv   pre-print
for emerging domains, such as digital assistants, cloud computing, and the internet of things.  ...  Finally, we highlight open research opportunities and challenges and take a broader perspective of the research by discussing the potential for intelligent software web agents as an enabling technology  ...  While, Palmirani et al. [2018] introduce their legal ontology that could be used to design privacy preserving intelligent agents.  ... 
arXiv:2102.06607v3 fatcat:5hqx4c6vevbonmyjetipw4ljyu

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims [article]

Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh (+47 others)
2020 arXiv   pre-print
stakeholders can take to improve the verifiability of claims made about AI systems and their associated development processes, with a focus on providing evidence about the safety, security, fairness, and privacy  ...  We analyze ten mechanisms for this purpose--spanning institutions, software, and hardware--and make recommendations aimed at implementing, exploring, or improving those mechanisms.  ...  Privacy-preserving machine learning aims to protect the privacy of data or models used in machine learning, at training or evaluation time and during deployment.  ... 
arXiv:2004.07213v2 fatcat:4xii6rzlyffjnj3nlb47tbqi4y

Information and the Regulatory Landscape: A Growing Need to Reconsider Existing Legal Frameworks

Anjanette Raymond
2018 Social Science Research Network  
See id. at 77 (describing treatment for maladaptive thinking). 211.  ...  Privacy by Design, also known as "data protection by design and by default," is the design approach that will soon become a legal requirement in the E.U. 182 Within the design approach, the use of technology-based  ...  Instead, policy makers and designers should begin to incorporate  ... 
doi:10.2139/ssrn.3349737 fatcat:kecyncp3ovdfneqfomjih4h6xu

Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour [article]

Emilia Gómez, Carlos Castillo, Vicky Charisi, Verónica Dahl, Gustavo Deco, Blagoj Delipetrev, Nicole Dewandre, Miguel Ángel González-Ballester, Fabien Gouyon, José Hernández-Orallo, Perfecto Herrera, Anders Jonsson, Ansgar Koene (+11 others)
2018 arXiv   pre-print
The workshop was organized in the context of a new research programme at the Centre for Advanced Studies, Joint Research Centre of the European Commission, which focuses on studying the potential impact  ...  Acknowledgements This workshop was organized by the Centre for Advanced Studies, Joint Research Centre with the local support of the Department of Information and Communication Technologies, Universitat  ...  The DL combined with Reinforcement learning (RL) won the game of GO, Atari, Poker and lastly Dota. DL and RL are rapidly expanding.  ... 
arXiv:1806.03192v1 fatcat:jypjtwtgxbg5vbkigudnxtsp64

Deep Reinforcement Learning: An Overview [article]

Yuxi Li
2018 arXiv   pre-print
Please see Deep Reinforcement Learning, arXiv:1810.06339, for a significant update.  ...  We start with background of machine learning, deep learning and reinforcement learning.  ...  Dynamic treatment regimes (DTRs) or adaptive treatment strategies are sequential decision making problems. Some issues in DTRs are not in standard RL.  ... 
arXiv:1701.07274v6 fatcat:x2es3yf3crhqblbbskhxelxf2q

Umjetna inteligencija kao segment strategije ili značenje (uloga) umjetne inteligencije u strategijskom planiranju

Nikola Anić, Petar Anić
2021 National security and the future  
One way of programming AI systems is 'reinforcement learning', where improved performance is reinforced with a virtual reward.  ...  If a patient has an open line of communication with their doctor, and engages in conversation about care and treatment, then the patient will trust the doctor.  ...  This is a publication of the Scientific Foresight Unit (STOA) EPRS | European Parliamentary Research Service This document is prepared for, and addressed to, the Members and staff of the European Parliament  ... 
doi:10.37458/nstf.21.3.4 fatcat:ppbbazo5qbcahhccwncus267ui
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