LÜBECK SUMMER ACADEMY HOW DOES AI TARGET CHALLENGES IN HEALTHCARE DIE SPEZIALISTEN FÜR KÜNSTLICHE INTELLIGENZ IM GESUNDHEITSWESEN

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1 DIE SPEZIALISTEN FÜR KÜNSTLICHE INTELLIGENZ IM GESUNDHEITSWESEN LÜBECK SUMMER ACADEMY ON MEDICAL TECHNOLOGY HOW DOES AI TARGET CHALLENGES IN HEALTHCARE FUSE-AI BERGSTRAßE HAMBURG F M JULY 2017

2 Mission and Vision Vision We want to secure and improve the quality of the healthcare system with intelligent solutions Mission Bringing AI based tools to the (German / European) market APPLICATIONS May

3 High Healthcare Spending in Germany Healthcare Spending in Percent of GDP Netherlands France Germany Switzerland Denmark Austria Belgium Portugal Sweden UK Spain Norway Italy Greece Iceland Finland Germany belongs to the countries with the highest spending of GDP on healthcare within Europe. Source: Die Welt APPLICATIONS May

4 Upward Trend of Health Expenditure in Germany Development of German Health Expenditure in billion Euro 58,1 % Statutory health insurance 13,4 % Private households 8,9 % Private health insurance 8,1 % Social care insurance 11,5 % Others Health spending is steadily increasing resulting in the need to improve efficiency of health insurance funds and healthcare providers. APPLICATIONS May

5 Approaches to Increase Efficiency in Healthcare Orientation towards a value-based healthcare system 1 : Value = Outcome Cost A higher value can be achieved by either improving patient outcomes or reducing cost while keeping outcome constant. Short-term approaches: - Process optimizations Long-term approaches: - Strengthen new technologies securing and increasing healthcare quality - Set focus on prevention and early diagnosis of diseases leading to improved patient outcomes and reduced costs Source: 1) Porter, M. E., What is Value in Health Care? (2009) APPLICATIONS May

6 Imaging Techniques increase strongly CT / MRT In Mio Number of Imaging Techniques is strongly increasing (CAGR 5.7%) CT MRT Increase of practising radiologists stays behind (CAGR 2.8%) Radiologists Workload of radiologists is growing as less radiologists perform more MRTs and CTs. APPLICATIONS May

7 Strategies to Increase Efficiency in Radiology Practices Contemporary technical equipment and software - allows for shorter examination times - is attractive to patients and medical staff Efficient use of the resources - machines - staff - energy Attractive services for private patients - contribute stronger to revenue Source: André Hoppen in European Hospital (2013) APPLICATIONS May

8 AI - The solution to all our problems How AI targets the main challenges in healthcare Lower rate of misdiagnosis, no fatigue Reduced time requirement for radiologists per patient Second Opinion In real-time and constant performance Value = Outcome Cost Allow higher utilisation of medical equipment Recognition of comorbidities Integrable digital solution (data barriers) 8

9 Solution: AI Platform SherLog Workflow 1. Project Phase 2. Utilization Phase Product properties Customized Reliable Easy to use Connectable Secure APPLICATIONS July

10 SherLog Architecture APPLICATIONS July

11 Summary: AI targets main challenges in healthcare Challenges: Value-based healthcare system demands for efficient solutions, that either reduce costs or increase patient outcome Solution: AI has a long research history Todays computing power along with huge amount of healthcare data enables this technology for commercial applications Main benefits include: Enhanced productivity Higher diagnostic accuracy Improved patient outcomes 11

12 AI - The solution to all our problems How AI targets the main challenges in healthcare Enhance quality in diagnosis Reduce time requirement for radiologists per patient Second Opinion Recognize comorbidities Ensure high quality of medical treatment Allow higher utilisation of MedTech Integrable digital solution (data barriers) 12

13 Team FUSE-AI is optimally positioned with a interdisciplinary team Matthias Steffen Founder 30 years of experience in Communication and Software development Founder of digital communications agency FUSE in 1996 Founder of the FUSE-Healthcare Unit 2011 Extensive experience in Keynotes for DEUTSCHE TELEKOM Co-organizer of Medical App Award 2016 (with Life Science Nord) Customer Service for: Auswärtiges Amt, Asklepios, Almirall, Allergopharma, Apotheker Verband, Deutsche Telekom, KPMG, Olympus Medical Maximilian Waschka Founder, Product Owner Very good contacts to companies and start-ups, working with Deep Learning Technology in London, San Francisco and Germ Extensive Knowledge in Account and Product Management Extensive knowledge of Business Models for Implementation and Developme of Deep Learning Algorithms and Embedded Vision Systems in Healthcare Bachelor of Cultural Studies (Media- and Cultural-Technologies; Art and Visual Culture) May

14 Team FUSE-AI is optimally positioned with a interdisciplinary team Dirk Schäfer Co-Founder, Machine Learning Engineer PhD candidate in AI/machine learning: preference learning Passion for machine learning methods in healthcare Extensive experience in the field of software engineering and systems architecture (DevOps) Diploma in computer science (University of Marburg, Germany): focus on knowledge discovery in databases Dr. rer.nat. Sabrina Reimers-Kipping Co-Founder, Molecular Biologist, Product Management Graduated biochemist with academic training in business administration and Passion for data-driven (economic) decisions and the possibility to improve health care with artificial intelligence solutions 6 years experience in medical basic research with focus on molecular and cell biology 3 years experience in marketing and business development in the life science sector Participating in Bachelors program for business administration and marketing 14