Agents and robots for collaborating and supporting physicians in healthcare scenarios
[Display omitted] •Multi-Agent system architectures for collaborative work in medical environments.•Monitoring patients through robotics telehealth system.•Assisting physicians in complex and dynamic clinical scenarios.•Human-Robot teaming interaction in clinical scenarios.•Intelligent agents deploy...
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Veröffentlicht in: | Journal of biomedical informatics 2020-08, Vol.108, p.103483-103483, Article 103483 |
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creator | Lanza, Francesco Seidita, Valeria Chella, Antonio |
description | [Display omitted]
•Multi-Agent system architectures for collaborative work in medical environments.•Monitoring patients through robotics telehealth system.•Assisting physicians in complex and dynamic clinical scenarios.•Human-Robot teaming interaction in clinical scenarios.•Intelligent agents deployed in the environment.•Runtime changing therapies.
Monitoring patients through robotics telehealth systems is an interesting scenario where patients’ conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems’ features to include the ability to serve patients with their needs, operating as human caregivers. The objective is to support the independent living of patients at home without losing the opportunity to monitor their health status. Application scenarios are several, and they spread from simple clinical assisting scenarios to an emergency one. For instance, in the case of a nursing home, the system would support in continuously monitoring the elderly patients. In contrast, in the case of an epidemic diffusion, such as COVID-19 pandemic, the system may help in all the early triage phases, significantly reducing the risk of contagion. However, the system has to let medical assistants perform actions remotely such as changing therapies or interacting with patients that need support. The paper proposes and describes a multi-agent architecture for intelligent medical care. We propose to use the beliefs-desires-intentions agent architecture, part of it is devised to be deployed in a robot. The result is an intelligent system that may allow robots the ability to select the most useful plan for unhandled situations and to communicate the choice to the physician for his validation and permission. |
doi_str_mv | 10.1016/j.jbi.2020.103483 |
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•Multi-Agent system architectures for collaborative work in medical environments.•Monitoring patients through robotics telehealth system.•Assisting physicians in complex and dynamic clinical scenarios.•Human-Robot teaming interaction in clinical scenarios.•Intelligent agents deployed in the environment.•Runtime changing therapies.
Monitoring patients through robotics telehealth systems is an interesting scenario where patients’ conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems’ features to include the ability to serve patients with their needs, operating as human caregivers. The objective is to support the independent living of patients at home without losing the opportunity to monitor their health status. Application scenarios are several, and they spread from simple clinical assisting scenarios to an emergency one. For instance, in the case of a nursing home, the system would support in continuously monitoring the elderly patients. In contrast, in the case of an epidemic diffusion, such as COVID-19 pandemic, the system may help in all the early triage phases, significantly reducing the risk of contagion. However, the system has to let medical assistants perform actions remotely such as changing therapies or interacting with patients that need support. The paper proposes and describes a multi-agent architecture for intelligent medical care. We propose to use the beliefs-desires-intentions agent architecture, part of it is devised to be deployed in a robot. The result is an intelligent system that may allow robots the ability to select the most useful plan for unhandled situations and to communicate the choice to the physician for his validation and permission.</description><identifier>ISSN: 1532-0464</identifier><identifier>EISSN: 1532-0480</identifier><identifier>DOI: 10.1016/j.jbi.2020.103483</identifier><identifier>PMID: 32603793</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; Artificial Intelligence ; Computer Systems ; Coronavirus Infections - therapy ; COVID-19 ; Emergency Medicine - instrumentation ; Geriatrics - instrumentation ; Human-robot interaction ; Humans ; Infectious Disease Medicine - instrumentation ; Medical Informatics ; Models, Theoretical ; Monitoring, Physiologic - instrumentation ; Monitoring, Physiologic - methods ; Multi-agent systems ; Nursing Homes ; Pandemics ; Patient monitoring ; Pneumonia, Viral - therapy ; Risk ; Robotics - trends ; Robots in Emergency Care for COVID-19 ; Robots in therapy ; Telemedicine - instrumentation ; Telemedicine - methods</subject><ispartof>Journal of biomedical informatics, 2020-08, Vol.108, p.103483-103483, Article 103483</ispartof><rights>2020 Elsevier Inc.</rights><rights>Copyright © 2020 Elsevier Inc. All rights reserved.</rights><rights>2020 Elsevier Inc. All rights reserved. 2020 Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c451t-bc395caa797fbf81e2eff20c2a3af5a535be3e4c6fc716102bc783bd87ad71423</citedby><cites>FETCH-LOGICAL-c451t-bc395caa797fbf81e2eff20c2a3af5a535be3e4c6fc716102bc783bd87ad71423</cites><orcidid>0000-0003-4382-6366</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1532046420301118$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32603793$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lanza, Francesco</creatorcontrib><creatorcontrib>Seidita, Valeria</creatorcontrib><creatorcontrib>Chella, Antonio</creatorcontrib><title>Agents and robots for collaborating and supporting physicians in healthcare scenarios</title><title>Journal of biomedical informatics</title><addtitle>J Biomed Inform</addtitle><description>[Display omitted]
•Multi-Agent system architectures for collaborative work in medical environments.•Monitoring patients through robotics telehealth system.•Assisting physicians in complex and dynamic clinical scenarios.•Human-Robot teaming interaction in clinical scenarios.•Intelligent agents deployed in the environment.•Runtime changing therapies.
Monitoring patients through robotics telehealth systems is an interesting scenario where patients’ conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems’ features to include the ability to serve patients with their needs, operating as human caregivers. The objective is to support the independent living of patients at home without losing the opportunity to monitor their health status. Application scenarios are several, and they spread from simple clinical assisting scenarios to an emergency one. For instance, in the case of a nursing home, the system would support in continuously monitoring the elderly patients. In contrast, in the case of an epidemic diffusion, such as COVID-19 pandemic, the system may help in all the early triage phases, significantly reducing the risk of contagion. However, the system has to let medical assistants perform actions remotely such as changing therapies or interacting with patients that need support. The paper proposes and describes a multi-agent architecture for intelligent medical care. We propose to use the beliefs-desires-intentions agent architecture, part of it is devised to be deployed in a robot. The result is an intelligent system that may allow robots the ability to select the most useful plan for unhandled situations and to communicate the choice to the physician for his validation and permission.</description><subject>Aged</subject><subject>Artificial Intelligence</subject><subject>Computer Systems</subject><subject>Coronavirus Infections - therapy</subject><subject>COVID-19</subject><subject>Emergency Medicine - instrumentation</subject><subject>Geriatrics - instrumentation</subject><subject>Human-robot interaction</subject><subject>Humans</subject><subject>Infectious Disease Medicine - instrumentation</subject><subject>Medical Informatics</subject><subject>Models, Theoretical</subject><subject>Monitoring, Physiologic - instrumentation</subject><subject>Monitoring, Physiologic - methods</subject><subject>Multi-agent systems</subject><subject>Nursing Homes</subject><subject>Pandemics</subject><subject>Patient monitoring</subject><subject>Pneumonia, Viral - therapy</subject><subject>Risk</subject><subject>Robotics - trends</subject><subject>Robots in Emergency Care for COVID-19</subject><subject>Robots in therapy</subject><subject>Telemedicine - instrumentation</subject><subject>Telemedicine - methods</subject><issn>1532-0464</issn><issn>1532-0480</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UU1rGzEQFaWl-Wh_QC9lj7nY0edql0IghDYtBHJpzmKkHdkya2krrQP595Xj1CSXnmaGefPezDxCvjC6ZJS1l5vlxoYlp3xfC9mJd-SUKcEXVHb0_TFv5Qk5K2VDKWNKtR_JieAtFboXp-TheoVxLg3EocnJppr6lBuXxhFsyjCHuHpult00pfxcTuunElyAWJoQmzXCOK8dZGyKwwg5pPKJfPAwFvz8Es_Jw4_vv29-Lu7ub3_dXN8tnFRsXlgneuUAdK-99R1Djt5z6jgI8AqUUBYFStd6p1nLKLdOd8IOnYZBM8nFObk68E47u8Whys8ZRjPlsIX8ZBIE87YTw9qs0qPRgtNO6Upw8UKQ058dltlsQ72iHh8x7YrhkvWyKvWyQtkB6nIqJaM_yjBq9naYjal2mL0d5mBHnfn6er_jxL__V8C3AwDrlx4DZlNcwOhwCBndbIYU_kP_F66hnbQ</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Lanza, Francesco</creator><creator>Seidita, Valeria</creator><creator>Chella, Antonio</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4382-6366</orcidid></search><sort><creationdate>20200801</creationdate><title>Agents and robots for collaborating and supporting physicians in healthcare scenarios</title><author>Lanza, Francesco ; Seidita, Valeria ; Chella, Antonio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-bc395caa797fbf81e2eff20c2a3af5a535be3e4c6fc716102bc783bd87ad71423</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aged</topic><topic>Artificial Intelligence</topic><topic>Computer Systems</topic><topic>Coronavirus Infections - therapy</topic><topic>COVID-19</topic><topic>Emergency Medicine - instrumentation</topic><topic>Geriatrics - instrumentation</topic><topic>Human-robot interaction</topic><topic>Humans</topic><topic>Infectious Disease Medicine - instrumentation</topic><topic>Medical Informatics</topic><topic>Models, Theoretical</topic><topic>Monitoring, Physiologic - instrumentation</topic><topic>Monitoring, Physiologic - methods</topic><topic>Multi-agent systems</topic><topic>Nursing Homes</topic><topic>Pandemics</topic><topic>Patient monitoring</topic><topic>Pneumonia, Viral - therapy</topic><topic>Risk</topic><topic>Robotics - trends</topic><topic>Robots in Emergency Care for COVID-19</topic><topic>Robots in therapy</topic><topic>Telemedicine - instrumentation</topic><topic>Telemedicine - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lanza, Francesco</creatorcontrib><creatorcontrib>Seidita, Valeria</creatorcontrib><creatorcontrib>Chella, Antonio</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of biomedical informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lanza, Francesco</au><au>Seidita, Valeria</au><au>Chella, Antonio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Agents and robots for collaborating and supporting physicians in healthcare scenarios</atitle><jtitle>Journal of biomedical informatics</jtitle><addtitle>J Biomed Inform</addtitle><date>2020-08-01</date><risdate>2020</risdate><volume>108</volume><spage>103483</spage><epage>103483</epage><pages>103483-103483</pages><artnum>103483</artnum><issn>1532-0464</issn><eissn>1532-0480</eissn><abstract>[Display omitted]
•Multi-Agent system architectures for collaborative work in medical environments.•Monitoring patients through robotics telehealth system.•Assisting physicians in complex and dynamic clinical scenarios.•Human-Robot teaming interaction in clinical scenarios.•Intelligent agents deployed in the environment.•Runtime changing therapies.
Monitoring patients through robotics telehealth systems is an interesting scenario where patients’ conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems’ features to include the ability to serve patients with their needs, operating as human caregivers. The objective is to support the independent living of patients at home without losing the opportunity to monitor their health status. Application scenarios are several, and they spread from simple clinical assisting scenarios to an emergency one. For instance, in the case of a nursing home, the system would support in continuously monitoring the elderly patients. In contrast, in the case of an epidemic diffusion, such as COVID-19 pandemic, the system may help in all the early triage phases, significantly reducing the risk of contagion. However, the system has to let medical assistants perform actions remotely such as changing therapies or interacting with patients that need support. The paper proposes and describes a multi-agent architecture for intelligent medical care. We propose to use the beliefs-desires-intentions agent architecture, part of it is devised to be deployed in a robot. The result is an intelligent system that may allow robots the ability to select the most useful plan for unhandled situations and to communicate the choice to the physician for his validation and permission.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32603793</pmid><doi>10.1016/j.jbi.2020.103483</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-4382-6366</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aged Artificial Intelligence Computer Systems Coronavirus Infections - therapy COVID-19 Emergency Medicine - instrumentation Geriatrics - instrumentation Human-robot interaction Humans Infectious Disease Medicine - instrumentation Medical Informatics Models, Theoretical Monitoring, Physiologic - instrumentation Monitoring, Physiologic - methods Multi-agent systems Nursing Homes Pandemics Patient monitoring Pneumonia, Viral - therapy Risk Robotics - trends Robots in Emergency Care for COVID-19 Robots in therapy Telemedicine - instrumentation Telemedicine - methods |
title | Agents and robots for collaborating and supporting physicians in healthcare scenarios |
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