Munich / Berlin, 04.07.2019 – Whether it is about prevention, early diagnosis or optimal therapeutic choice, artificial intelligence and machine learning can contribute significantly to the providing better and more personalized medical care in the near future. The report illustrates the potential of technologies with the help of research examples and an application scenario on lung cancer. "Physicians can, for example, more accurately assess imaging techniques with the help of AI systems or consult learner systems to choose the appropriate treatment – but the power of decision must belong to the specialized staff, "says Klemens Budde, site manager of Campus Charité Mitte and his colleagues. Head of the working group.
The report also highlights the interaction between humans and the machine in nursing: AI-assisted language acquisition could relieve caregivers of routine tasks such as documentation; This would leave more time for human attention. Support robots and artificial intelligence-based technologies such as exoskeletons could also allow people to live in the future and self-determine.
Make everyday life healthier with AI
Medical applications for AI are not the only ones to enable people with cancer: smartphone apps or wearable devices also offer healthy people the opportunity to save and d & # 39; Evaluate their own health data. On this basis, people can improve their daily lives or identify the symptoms of the disease sooner. Particularly in the prevention and early detection of diseases, KI therefore has significant potential.
Members of the working group from science, industry, health insurance companies, social enterprises and patient representatives also identify the main challenges related to the use of health and safety systems. Learning in health and health care. "The key lies in data of sufficient quantity and quality, we need a representative, controlled health database with information on all sectors of the health system." the image of some European countries is a smart approach, we should also discuss options for a secure and self-determined data donation, "said Budde. The donation of data should be based on the principles of voluntarism and autonomy, so that your health is not paid with sensitive data, says the report.
In addition, experts point out that professional profiles will change because of new technological possibilities. In order to be able to use AI-based applications in the diagnosis or choice of a therapy responsibly, basic knowledge in the field of machine learning and technology is the most important. information is needed. The physician-patient relationship will also change as algorithms facilitate decision-making and patients become more actively involved in data collection and evaluation. "The excellent basic research and applications is the foundation that will allow us to unleash the potential of learning systems.In order to introduce innovation into the daily lives of doctors and nurses, it is skills are needed: digital health programs or training programs should be expanded, as well as ongoing training of staff and patient training, "said Karsten Hiltawsky, Head of the Department of Technology and Training. intellectual property of Drägerwerk AG & Co. KGaA and co-leader of the working group.
In order to bring innovation to the patient, one must also answer regulatory questions. Because the licensing of medical and nursing learning systems creates specific challenges. "Learning systems are changing on the fly as they are constantly learning new data, and current regulations for clinical trials and certification of medical devices do not yet cover this case." C & # 39; This is why new rules need to be developed for the learning of medical devices that provide legal certainty for companies, "says Karsten Hiltawsky.
The authors emphasize that the benefits for patients and those in need of care must be at the center of technological achievements. "Artificial intelligence applications are designed to support, not replace, hospital and nursing professionals, because communication and empathy play a vital role in medicine and nursing. not replacing human attention – but it is able to relieve staff of routine activities, which gives more time to talk to patients, "says Budde.
In its report, the Health, Medical Technology and Nursing Working Group offers design options to exploit the opportunities offered by health and care learning systems. These range from setting up appropriate infrastructures such as a health database and decentralized architectures, to developing skills in research, development and applications, creating standards. for clinical trials and regulatory approvals and the resolution of ethical issues. The report is available for download at https://www.plattform-lernende-systeme.de/files/Downloads/Publikationen/AG6_Bericht_23062019.pdf.
About the Learning Systems Platform
The platform Lernende Systeme was founded in 2017 by the Federal Ministry of Education and Research (BMBF) at the suggestion of the Forum on Autonomous Systems Forum of High Technology and acatech. It brings together experts from the fields of science, business, politics and civil society in the field of artificial intelligence. In working groups, they develop options for action and recommendations for the responsible use of learning systems. The objective of the platform is to promote social dialogue as an independent intermediary, to stimulate cooperation in research and development and to position Germany as the leading technology provider for learning systems. The platform is managed by Federal Minister Anja Karliczek (BMBF) and Karl-Heinz Streibich (Acatech President).