Artificial inteligence in medicine
Artificial intelligence (AI) technologies belong to the fourth stage of the Industrial Revolution that we have recently entered. There are many promising applications for AI in health care, addressing a variety of aims and taking many different approaches. [1,2] AI-based technologies employing deep-learning (DL) approaches have proven effective in supporting decisions in many medical specialties, including radiology, cardiology, oncology, dermatology, ophthalmology, and others. [1,2] For example, AI/DL algorithms (also referred to as AI/DL models in the following text) have been shown to reduce waiting times, improve medication adherence, customize insulin dosages, and help interpret magnetic resonance images. The number of AI life-science papers listed in PubMed increased from 596 in 2010 to 12,422 in 2019 .
AI-research is based on access to high-reliability and relatively big datasets what makes the scientific collaboration and networking crucial for this field. As a matter of fact, it was recently pointed that networking is one of success factors in AI-related technologies in such countries like USA, Singapur and China.  Thus, we believe that it is important to create a Pan-European network for AI in life sciences to better coordinate the possible collaboration in this area. For this purpose we propose to establish a working group on AI in life-sciences within the Academia Europaea.
- Grzybowski A. Artificial Intelligence in Ophthalmology: Promises, Hazards and Challenges. Artificial Intelligence in Ophthalmology. Springer 2021, Cham. https://doi.org/10.1007/978-3-030-78601-4
- Topol E. Deep medicine: how artificial intelligence can make healthcare human again. New York: Basic Books; 2019.
- Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ Digit Med. 2020;3:118
- Boudry C, Al Hajj H, Arnould L, Mouriaux F. Analysis of international publication trends in artificial intelligence in ophthalmology. Graefes Arch Clin Exp Ophthalmol. 2022 May;260(5):1779-1788.