چکیده: (112 مشاهده)
Background: Artificial intelligence (AI) is increasingly recognized as a transformative technology in healthcare innovation and digital health ecosystems. Health technology incubators play a key role in supporting startups and translating innovations into clinical and commercial solutions, yet the integration of AI within these ecosystems remains underexplored.
Methods: A narrative review was conducted to examine the role of AI in health technology incubators. Relevant literature was identified through searches of major scientific databases, including PubMed, Scopus, Web of Science, and Google Scholar. The selected literature was screened for relevance and synthesized thematically.
Results: The findings indicate that AI can enhance health technology incubators through applications in business model innovation, health product development, clinical data analysis, policy-related decision-making, startup selection, and performance evaluation. Successful implementation requires adequate data resources, technological infrastructure, and a skilled workforce. Key challenges include ethical, legal, and governance issues, particularly those related to privacy, transparency, and accountability.
Conclusion: AI has the potential to improve the efficiency, effectiveness, and sustainability of health technology incubators by accelerating innovation and strengthening startup development. However, its successful adoption depends on robust infrastructure, governance frameworks, and further empirical validation in real-world settings.
Methods: A narrative review was conducted to examine the role of AI in health technology incubators. Relevant literature was identified through searches of major scientific databases, including PubMed, Scopus, Web of Science, and Google Scholar. The selected literature was screened for relevance and synthesized thematically.
Results: The findings indicate that AI can enhance health technology incubators through applications in business model innovation, health product development, clinical data analysis, policy-related decision-making, startup selection, and performance evaluation. Successful implementation requires adequate data resources, technological infrastructure, and a skilled workforce. Key challenges include ethical, legal, and governance issues, particularly those related to privacy, transparency, and accountability.
Conclusion: AI has the potential to improve the efficiency, effectiveness, and sustainability of health technology incubators by accelerating innovation and strengthening startup development. However, its successful adoption depends on robust infrastructure, governance frameworks, and further empirical validation in real-world settings.
نوع مقاله: مروری |
دریافت: 1404/10/25 | پذیرش: 1404/12/29
دریافت: 1404/10/25 | پذیرش: 1404/12/29
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