Philipp Dumbach (M.Sc.), Prof. Dr. Björn Eskofier, Max Jalowski (M. Sc.), Prof. Dr. Kathrin Möslein
Artificial intelligence (AI) has changed our life dramatically in many areas over decades. The healthcare industry can be named as popular area, in which AI concepts, techniques and tools were utilized to benefit healthcare by assisting healthcare professionals in improving their effectiveness, productivity, and consistency.  A major application of AI in healthcare is collecting, storing, normalizing, and tracing data.  Based on this, AI has already been implemented in plenty of medical applications, either more traditional ones like diagnosis, imaging-guided robot-assisted surgery, support of correct medical decisions, or more recent ones include disease genes, wearable medical devices or surgery simulation. [1, 3, 4] In future, there is little doubt that AI will further revolutionize the way healthcare practitioners and executives gather information and interact with patients and their families, as well as with clinical and operational staff. 
To gather an overview on the adoption of AI in healthcare, it is meaningful to subdivide the research groups according to the scale of companies. This study focuses on SMEs and will select several healthcare startups, in order to detect how the chosen startups are influenced by adopting AI technologies in the framework of a qualitative-empirical case study. A formal prepared protocol including the study overview, data collection procedures as well as research questions will be developed as a major way of increasing the reliability.  The data collection method is a semi-structured interview, in which several open-ended questions in the field of AI adoption will be asked. 
The aim of this qualitative study is to identify the situation on adoption of AI for healthcare startups and further detect the future trends. Based on this, the following questions will be answered: during the past period of using AI, in which specific processes the startups have benefited from AI, meanwhile in which aspects they may have the most challenges while applying AI technologies in products and services. Furthermore, what kind of further development the startups are expecting in the field of AI technology in healthcare. Based on the interview results, a further analysis on how startups could better prepare for the opportunities in the near future will be performed.
 Agah, A. (2014): Medical Applications of Artificial Intelligence. Boca Raton: CRC Press.
 Mesko, B. (2017): The role of artificial intelligence in precision medicine. Expert Review of Precision Medicine and Drug Development 2 (5), pp. 239–241.
 Ranschaert, Erik R., Morozov, S., Algra, Paul R. (2019): Artificial Intelligence in Medical Imaging. Springer International Publishing.
 Kohn, Steven M. (2018): Editorial commentary: Wearable Devices and Personalized Healthcare. Trends in cardiovascular medicine 28 (2), pp. 151–152.
 Garbuio, M., Lin, N. (2019): Artificial Intelligence as a Growth Engine for Health Care Startups: Emerging Business Models. California Management Review 61 (2), pp. 59–83.
 Yin, Robert K. (2018): Case study research and applications: design and methods. SAGE Publications, Inc.
 Edwards, R., Holland, J. (2013): What is qualitative interviewing? London, New Delhi: Bloomsbury.