PhilHumans · Personal Health Interfaces Leveraging Human-Machine Natural Interactions
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2019-01-01 → 2023-10-31
- Финансиране от ЕС
- 2 135 436 €
- Участници
- 16
- Схема
- MSCA-ITN
Линиите свързват координатора с партньорите.
Накратко на български
Интерфейси между човек и машина изследват как изкуственият интелект, разпознаването на изображения и езика могат да направят работата с личните здравни устройства по-интуитивна. Това помага за подобряване на грижите за здравето у дома и управлението на здравето на населението.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Personal Health Interfaces Leveraging Human-Machine Natural Interactions
The PhilHumans project has trained a next generation of young researchers in innovative Artificial Intelligence (AI) and establish user interaction with their personal health devices in an advanced and intuitive way. The project explored cutting-edge research topics related to AI-supported human-machine interfaces for personal health services. PhilHumans has committed to responsible research and innovation to establish disruptive and innovative technology for AI-assisted human-machines interfaces, employing language technology, cognitive computing, computer vision, and machine learning (ML). The technology can be applied in a number of personal health contexts and extend or being coupled with Home healthcare, as well as in additional fields such as population health management and provide several benefits to users making sure science and research is conducted with and for society. The training and research network with 8 ESR in the project explored AI knowledge and expertise from Natural Language Generation (NLG) & Processing (NLP), Cognitive Computing, Computer Vision, ML focusing on 5 research objectives. Based on sound career development plans, and coached by experienced supervisors a training was offered by leading image analysis research groups from Philips (global leader in medical imaging) and the Eindhoven university of Technology (worldwide recognized authority in education and research on image analysis, esp. on MRI) and supported by researchers from leading universities like University of Cagliari, University of Catania and University of Aberdeen. After finalisation of their PhD the researchers plan for a next career step in research or industry depending on their affinity. The project has contributed to the development of innovative technologies, data sets, and application concepts in the area of personal health interfaces. The work has been documented in the top conferences and journals in the area and many of the results, including data sets developed in the project, and software repositories, are available for the further research and development work in the community.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
The goal of the PhilHumans (Personal Health Interfaces Leveraging Human-MAchine Natural interactionS) project is to train a next generation of young researchers in innovative Artificial Intelligence (AI) and establish user interaction with their personal health devices in an advanced and intuitive way. PhilHumans will investigate cutting-edge AI methods for human-machine interaction in the personal health domain through a well-designed and structured research training programme, with the aim to enhance EU firms competitiveness in the field for an effective and lasting market penetration in EU.The research in PhilHumans will be performed by an intersectoral and multidisciplinary consortium consisting of 8 ESRs and a team of supervisors from the academic beneficiaries (University of Cagliari, University of Catania, University of Aberdeen, and Technical University of Eindhoven (TU/e)), the industrial beneficiaries (PHILIPS and R2M), and other external partners. The project will require the creation of a blend of interdisciplinary understanding of personal digital assistant, cognitive computing, (deep) machine learning, natural language generation & processing, advanced computer vision, and business development. The personal health areas that will be investigated are Mother&Child care, healthy-living and personal care, where the application of the proposed technology has promising potential.All ESRs will enroll in a 3-years PhD research programme at beneficiary academic institutions. They are supposed to act as an integrated and complementary expertize team, whose aim is to tackle the fundamental challenge of combining heterogeneous data sources from multilingual speech/text processing and computer vision for improving conversation, detecting emotions, and improving social interactions. All the academic ESRs for at least 50% of their time will attend their secondment at PHILIPS, which will provide the required infrastructure and supervision by senior research staff.
Оригинален текст от CORDIS (на английски).
Участници
- PHILIPS ELECTRONICS NEDERLAND BV · EindhovenКоординаторНидерландия
- ARRIA NLG (UK) LIMITED · LondonОбединеното кралство
- FONDAZIONE BRUNO KESSLER · TrentoИталия
- Philips Electronics North America Corporation · WilmingtonСъединени щати
- R2M SOLUTION SPAIN SL · MadridИспания
- TECHNISCHE UNIVERSITEIT DELFT · DelftНидерландия
- TECHNISCHE UNIVERSITEIT EINDHOVEN · EindhovenНидерландия
- THE UNIVERSITY COURT OF THE UNIVERSITY OF ABERDEEN · AberdeenОбединеното кралство
- TILBURG UNIVERSITY- UNIVERSITEIT VAN TILBURG · TilburgНидерландия
- UNIVERSITA DEGLI STUDI DI CAGLIARI · CagliariИталия
- UNIVERSITA DEGLI STUDI DI CATANIA · CataniaИталия
- UNIVERSITA DEGLI STUDI DI PAVIA · PaviaИталия
- UNIVERSITE PARIS 13 · VilletaneuseФранция
- UNIVERSITY OF ESSEX · ColchesterОбединеното кралство
- UNIVERSITY OF GALWAY · GalwayИрландия
- Zora Robotics N.V. · OostendeБелгия
Връзки
- Виж в CORDIS
- DOI: 10.3030/812882
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5048df2d2&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5048e47ec&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50c12c04e&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50c64e217&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5c1f8e642&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5c1f9125c&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5c55f8f78&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5ccb58638&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5cfa19189&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5d944521a&appId=PPGMS
Данни: CORDIS, © Европейски съюз
