Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries

Transferability of new methods for health technology assessment in the field of diabetes between early and late adopters’ countries

This study aimed to investigate the transferability of novel artificial intelligence (AI) methods for prediction modelling of diabetes based on real-world data (RWD) between early and late adopters of emerging health technologies from the perspective of developers and health technology assessment (H...

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Main Authors: Konstantin Tachkov, Francisco Somolinos-Simón, Jose Tapia-Galisteo, Maria Elena Hernando, Gema García-Sáez, Maria Dimitrova, Maria Kamusheva, Zornitsa Mitkova, Zsuzsanna Petyko, Bertalan Nemeth, Zoltan Kalo, Tomas Tesar, Marian-Sorin Paveliu, Oresta Piniazhko, Iga Lipska, Adina Turcu-Stiolica, Alexandra Savova, Manoela Manova, Rok Hren, Petra Došenović Bonča, Saskia Knies, Michal Stanak, Tomáš Doležal, Dinko Vitezic, Guenka Petrova
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Biotechnology & Biotechnological Equipment
Subjects:
Transferability
health technology assessment
Central and Easter European Countries
diabetes
artificial intelligence
Online Access:https://www.tandfonline.com/doi/10.1080/13102818.2024.2371354
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