| dc.contributor.author | Bobes-Bascarán, José | |
| dc.contributor.author | Mosqueira-Rey, E. | |
| dc.contributor.author | Alonso Ríos, David | |
| dc.date.accessioned | 2022-01-03T11:40:44Z | |
| dc.date.available | 2022-01-03T11:40:44Z | |
| dc.date.issued | 2021 | |
| dc.identifier.citation | Bobes-Bascarán, J.; Mosqueira-Rey, E.; Alonso-Ríos, D. Improving Medical Data Annotation Including Humans in the Machine Learning Loop. Eng. Proc. 2021, 7, 39. https://doi.org/10.3390/engproc2021007039 | es_ES |
| dc.identifier.uri | http://hdl.handle.net/2183/29300 | |
| dc.description | Presented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021 | |
| dc.description.abstract | [Abstract] At present, the great majority of Artificial Intelligence (AI) systems require the participation of humans in their development, tuning, and maintenance. Particularly, Machine Learning (ML) systems could greatly benefit from their expertise or knowledge. Thus, there is an increasing interest around how humans interact with those systems to obtain the best performance for both the AI system and the humans involved. Several approaches have been studied and proposed in the literature that can be gathered under the umbrella term of Human-in-the-Loop Machine Learning. The application of those techniques to the health informatics environment could provide a great value on prognosis and diagnosis tasks contributing to develop a better health service for Cancer related diseases. | es_ES |
| dc.description.sponsorship | This work has been supported by the State Research Agency of the Spanish Government, grant (PID2019-107194GB-I00/AEI/10.13039/501100011033) and by the Xunta de Galicia, grant (ED431C 2018/34) with the European Union ERDF funds. We wish to acknowledge the support received from the Centro de Investigación de Galicia “CITIC”, funded by Xunta de Galicia and the European Union (European Regional Development Fund- Galicia 2014-2020 Program), by grant ED431G 2019/01 | es_ES |
| dc.description.sponsorship | Xunta de Galicia; ED431C 2018/34 | es_ES |
| dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | MDPI | es_ES |
| dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107194GB-I00/ES/ANALISIS DE ESTRATEGIAS PARA INCORPORAR HUMANOS AL PROCESO DE APRENDIZAJE AUTOMATICO Y SU APLICACION A LA INVESTIGACION DEL CANCER PANCREATICO | |
| dc.relation.uri | https://doi.org/10.3390/engproc2021007039 | es_ES |
| dc.rights | Atribución 4.0 Internacional | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Human-in-the-Loop | es_ES |
| dc.subject | Machine learning | es_ES |
| dc.subject | Interactive Machine Learning | es_ES |
| dc.subject | Machine Teaching | es_ES |
| dc.subject | Iterative Machine Teaching | es_ES |
| dc.subject | Active learning | es_ES |
| dc.title | Improving Medical Data Annotation Including Humans in the Machine Learning Loop | es_ES |
| dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
| dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
| UDC.journalTitle | Enineering Proceedings | es_ES |
| UDC.volume | 7 | es_ES |
| UDC.issue | 1 | es_ES |
| UDC.startPage | 39 | es_ES |
| dc.identifier.doi | 10.3390/engproc2021007039 | |
