Συνθετικά δεδομένα : ευκαιρίες και προκλήσεις εφαρμογής τους στον χώρο της υγείας
Synthetic data : opportunities and challenges for its application in healthcare
View/
Keywords
Συνθετικά δεδομένα ; Υγειονομική περίθαλψη ; Τεχνητή νοημοσύνη ; AI ; Προστασία δεδομένωνAbstract
The rapid digitilization of healthcare has generated vast amounts of patient data, creating unprecedented opportunities for research, clinical innovation, and personalized medicine. However, the use of real patient data is often limited by privacy concerns, limited accessibility, and regulatory restrictions. Synthetic data, artificially generated data that retains the statistical properties of real data sets without exposing sensitive information, has emerged as a promising solution to these challenges. This review explores the opportunities and challenges associated with the application of synthetic data in healthcare. Synthetic data offers multiple advantages, such as the ability to improve artificial intelligence (AI) models, support clinical research, enable predictive analytics, and facilitate the development of digital twins. By providing realistic but anonymous data sets, they can mitigate data shortages, support the training of machine learning algorithms, and accelerate the evaluation of innovative interventions. The availability of publicly accessible synthetic datasets and ready-made creation tools underscores the growing interesting of the use of synthetic data in research, software development, and innovation in the field of health informatics. Despite these opportunities, the adoption of synthetic data in healthcare sector faces significant challenges. Ensuring the fidelity, quality, and representativeness of synthetic datasets is crucial to avoid bias, misinterpretation, and incorrect decisions. Regulatory and ethical frameworks must evolve in parallel to protect patient privacy and maintain public trust. Users must carefully evaluate the suitability and limitations of synthetic datasets for their intended applications.