Scifed Cardiology-2018 conference.

Cyber Security in IT Hospitals

Cardiology-2018 conference.

Dr. Wellnhofer from Charité University Medicine Berlin, Berlin DE-13353, Germany. He is clinical cardiologist, scientist and university teacher. His fields of work are cardiac imaging in particular of coronary atherosclerosis, biomedical informatics and statistics, regulatory issues regarding software as medical device and health technology assessment. He published more than 90 papers in reputed journals and holds several patents. His h-index is 24. Dr. Wellnhofer was giving the Keynote Presentation on Cyber security is an increasing challenge in IT 4.0-hospitalsat 2nd International Congress and Expo on Cardiology (Cardiology-2018)Conference. A brief summary of his presentation here.

IT networks of hospitals are promising targets for cyber in particular ransom attacks, because short term availability of medical data may be of vital importance and confidentiality of health data is a regulatory issue (HIPAA). Since hospitals are open systems for patients, employees and other stakeholder’s risks for intrusion are not controlled by a perimeter defense alone. Moreover, the introduction of wireless networks (WIFI/WLAN) and a pervasive digital transformation of communication, processes and documentation enhance vulnerability. Executives under-invest in cyber security and staffing is critical as budget resources are limited.

Thus, professional risk management is of vital importance. An appropriate information security managements System (ISMS) may be installed and maintained according to ISO 27001 or national regulatory frameworks. This presentation covers some selective critical issues and first line considerations for small and medium sized companies/hospitals.

Dr. Wellnhofer was going to conduct a Workshop on Machine learning and Artificial Intelligence in Cardiac Imaging”. A brief summary of the workshop is here.

The workshop is interdisciplinary and spans from imaging in cardiology to sophisticated algorithms and new approaches in machine learning. Apart from reviewing the existing landscape brainstorming should comprise future perspectives.


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