Cargando…
OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care
OBJECTIVE: OpenClinical.net is a way of disseminating clinical guidelines to improve quality of care whose distinctive feature is to combine the benefits of clinical guidelines and other human-readable material with the power of artificial intelligence to give patient-specific recommendations. A key...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7388886/ https://www.ncbi.nlm.nih.gov/pubmed/32723855 http://dx.doi.org/10.1136/bmjhci-2020-100141 |
_version_ | 1783564385878278144 |
---|---|
author | Fox, John South, Matthew Khan, Omar Kennedy, Catriona Ashby, Peter Bechtel, John |
author_facet | Fox, John South, Matthew Khan, Omar Kennedy, Catriona Ashby, Peter Bechtel, John |
author_sort | Fox, John |
collection | PubMed |
description | OBJECTIVE: OpenClinical.net is a way of disseminating clinical guidelines to improve quality of care whose distinctive feature is to combine the benefits of clinical guidelines and other human-readable material with the power of artificial intelligence to give patient-specific recommendations. A key objective is to empower healthcare professionals to author, share, critique, trial and revise these ‘executable’ models of best practice. DESIGN: OpenClinical.net Alpha (www.openclinical.net) is an operational publishing platform that uses a class of artificial intelligence techniques called knowledge engineering to capture human expertise in decision-making, care planning and other cognitive skills in an intuitive but formal language called PROforma.3 PROforma models can be executed by a computer to yield patient-specific recommendations, explain the reasons and provide supporting evidence on demand. RESULTS: PROforma has been validated in a wide range of applications in diverse clinical settings and specialties, with trials published in high impact peer-reviewed journals. Trials have included patient workup and risk assessment; decision support (eg, diagnosis, test and treatment selection, prescribing); adaptive care pathways and care planning. The OpenClinical software platform presently supports authoring, testing, sharing and maintenance. OpenClinical’s open-access, open-source repository Repertoire currently carries approximately 50+ diverse examples (https://openclinical.net/index.php?id=69). CONCLUSION: OpenClinical.net is a showcase for a PROforma-based approach to improving care quality, safety, efficiency and better patient experience in many kinds of routine clinical practice. This human-centred approach to artificial intelligence will help to ensure that it is developed and used responsibly and in ways that are consistent with professional priorities and public expectations. |
format | Online Article Text |
id | pubmed-7388886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-73888862020-09-30 OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care Fox, John South, Matthew Khan, Omar Kennedy, Catriona Ashby, Peter Bechtel, John BMJ Health Care Inform Short Report OBJECTIVE: OpenClinical.net is a way of disseminating clinical guidelines to improve quality of care whose distinctive feature is to combine the benefits of clinical guidelines and other human-readable material with the power of artificial intelligence to give patient-specific recommendations. A key objective is to empower healthcare professionals to author, share, critique, trial and revise these ‘executable’ models of best practice. DESIGN: OpenClinical.net Alpha (www.openclinical.net) is an operational publishing platform that uses a class of artificial intelligence techniques called knowledge engineering to capture human expertise in decision-making, care planning and other cognitive skills in an intuitive but formal language called PROforma.3 PROforma models can be executed by a computer to yield patient-specific recommendations, explain the reasons and provide supporting evidence on demand. RESULTS: PROforma has been validated in a wide range of applications in diverse clinical settings and specialties, with trials published in high impact peer-reviewed journals. Trials have included patient workup and risk assessment; decision support (eg, diagnosis, test and treatment selection, prescribing); adaptive care pathways and care planning. The OpenClinical software platform presently supports authoring, testing, sharing and maintenance. OpenClinical’s open-access, open-source repository Repertoire currently carries approximately 50+ diverse examples (https://openclinical.net/index.php?id=69). CONCLUSION: OpenClinical.net is a showcase for a PROforma-based approach to improving care quality, safety, efficiency and better patient experience in many kinds of routine clinical practice. This human-centred approach to artificial intelligence will help to ensure that it is developed and used responsibly and in ways that are consistent with professional priorities and public expectations. BMJ Publishing Group 2020-07-28 /pmc/articles/PMC7388886/ /pubmed/32723855 http://dx.doi.org/10.1136/bmjhci-2020-100141 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Short Report Fox, John South, Matthew Khan, Omar Kennedy, Catriona Ashby, Peter Bechtel, John OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care |
title | OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care |
title_full | OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care |
title_fullStr | OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care |
title_full_unstemmed | OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care |
title_short | OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care |
title_sort | openclinical.net: artificial intelligence and knowledge engineering at the point of care |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7388886/ https://www.ncbi.nlm.nih.gov/pubmed/32723855 http://dx.doi.org/10.1136/bmjhci-2020-100141 |
work_keys_str_mv | AT foxjohn openclinicalnetartificialintelligenceandknowledgeengineeringatthepointofcare AT southmatthew openclinicalnetartificialintelligenceandknowledgeengineeringatthepointofcare AT khanomar openclinicalnetartificialintelligenceandknowledgeengineeringatthepointofcare AT kennedycatriona openclinicalnetartificialintelligenceandknowledgeengineeringatthepointofcare AT ashbypeter openclinicalnetartificialintelligenceandknowledgeengineeringatthepointofcare AT bechteljohn openclinicalnetartificialintelligenceandknowledgeengineeringatthepointofcare |