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Monday, November 28, 2022  /  Blog post

The University of Thessaly Plus is co-creating a new perspective for the next generation of health professionals!

The University of Thessaly Plus is co-creating a new perspective for the next generation of health professionals!

Authors: Vasiliki Softa, Ira Alevra

The University of Thessaly in collaboration with the Department of Medical Physics participates in the consortium of the project "AIIS: Artificial Intelligence, Innovation and Society" where with the collaboration of Higher Education Institutions and specialized companies in the field of technology from 5 European countries, a new perspective is formed for studies and a career in the field of Medicine. The project, with a total duration of three years, is funded by the European Education, Audiovisual and Culture Executive Agency (EACEA) and aims to create an educational training program in Artificial Intelligence and Social Skills specially designed for medical students and taking into account the current needs of branch in Spain, Finland, Greece, the Netherlands and Belgium.

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Monday, August 29, 2022  /  Project Updates

2022 August AIIS press release

2022 August AIIS press release

University of Salamanca (USAL) and the AIIS consortium presenting the first results of the Project AIIS: Artificial Intelligence, Innovation & Society. The project aims to improve medical students' digital & social skills with an innovative online program developed in cooperation with European Higher Education Institutions (HEIs) and companies around 5 European countries: Spain, Finland, Greece, Netherlands and Belgium. This training includes understanding the capabilities of Artificial Intelligence (AI) in today's medicine and training in Soft Skills, to encourage the confidence of healthcare professionals and society in AI.

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Wednesday, June 15, 2022  /  Blog post

Is fairness viable in AI healthcare applications?

Is fairness viable in AI healthcare applications?

Most artificial intelligence applications focus on optimizing their predictions. However, machine learning algorithms should not be focused solely on accuracy but should be evaluated with respect to how they might impact disparities in patient outcomes. AI researchers must explore ways to reduce machine learning bias in healthcare or explain how to create algorithms that specifically alleviate inequalities

To prevent artificial intelligence (AI) from encoding the disparities that exist, algorithms should predict an outcome as if the world were fair.

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Friday, June 3, 2022  /  Blog post

On the continuous need for artificial intelligence development and recalibration in medicine

On the continuous need for artificial intelligence development and recalibration in medicine

AI is increasingly present in hospital environments: applications for the automatic segmentation of medical images, algorithms to predict pathologies, hospital readmission or mortality are some of these examples. However, these models are susceptible to failure if they are not periodically reviewed. It is something similar to what we would do with our car after many kilometers of use, an overhaul or more specifically: quality control.

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AIIS contact email: aiis@usal.es

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