Digital Health Accelerator
AIgnostics - Computational Pathology
Microscopic evaluation of tissue samples performed by pathologists is the basis of diagnosing cancer as well as many degenerative, infectious and inflammatory diseases. Given our aging population, the increase in numbers and complexity of cancer cases worldwide, a global shortage of pathologists is imminent. As a result, the capacity of healthcare systems to perform histological diagnostics and determine the right therapy is under increasing pressure.
To address this challenge, team AIgnostics has developed an AI-based image analysis system to assist pathologists in standardized and quantitative automated tissue diagnostics. This solution promises to be more accurate and faster than today’s manual gold standard. The system can also be applied to drug development, where pharmaceutical companies depend on accurate assessments of histological tissue samples in preclinical animal studies or in clinical trials to stratify patients in drug efficacy and toxicity analyses.
Team AIgnostics consists of experts in the fields of diagnostic and computational pathology from Charité – Universitätsmedizin Berlin, in cooperation with Prof. Klaus-Robert Müller, a globally renowned expert in machine learning from Technical University Berlin.
Prof. Dr. Frederick Klauschen
Institute for Pathology CCM - Clinical Pathology, WG System Pathology, Charité – Universitätsmedizin Berlin
"The BIH Digital Health Accelerator enabled us to turn our research results on AI-based cancer diagnostics into practical application. Not only could we develop a software prototype that is currently tested live, but were also exposed to business, regulatory and legal aspects. While challenging us, this put us in a position to pursue a stringent development path towards launching our spin-off company in the near future. I highly recommend this program to researchers and clinicians looking to generate digital health innovations for better patient health outcomes."
BodyTime - A New Diagnostic Assay to Assess the Internal Clock
The biological clock is essential for health. The fast-paced and globalized lifestyles in modern society increasingly lead to the misalignment or disruption of our biological clock, which is associated with numerous common diseases such as sleep disorders, psychological disorders, metabolic syndromes, rheumatic disorders, cardiovascular diseases, and cancer.
In the emerging field of chronomedicine, team BodyTime addresses this medical need with a blood test (ChronoMarker) to determine the individual’s biological clock by profiling genetic biomarkers and applying machine-learning algorithms. While as accurate as currently established tests, this solution promises to be less complex, faster and more cost-effective. As the first application, the team is targeting sleep disorders in collaboration with sleep labs as a stand-alone tool or companion diagnostic for pharmaceutical or behavioral therapy options. Other opportunity areas include stratification of clinical trial cohorts, application to other disease types, and solutions directly empowering affected individuals.
Team BodyTime consists of experts in the field of chronobiology, medicine, and data-analysis / software development from Charité – Universitätsmedizin Berlin, supported by an expert in life sciences and new venture development.
Prof. Dr. Achim Kramer
Institute for Medical Immunology - Chronobiology, Charité – Universitätsmedizin Berlin
"DHA helped us to focus on issues scientists usually do not consider as too important - but they are important to move a technology towards market application. DHA was great in training and coaching us in a limited time frame with a high degree of knowledge and flexibility."
Press and Media Coverage
Cardio Prime - Diagnosis and Therapy Planning Platform for Patients with Cardiovascular Diseases
The care path for cardiovascular patients, ranging from symptom detection to diagnosis to therapy and disease management, is fragmented. Providing each patient with the right type of care at the right place of care is a key challenge for each healthcare system. In a fragmented cardiovascular care path, quality and efficiency of care suffer.
Team Cardio Prime has developed an innovative Digital Health platform for diagnosis and therapy planning to inform and improve the care path for patients with cardiovascular diseases. The solution enables physicians working in cardiovascular and other specialties at hospitals, in specialist practices and in general practices to diagnose cardiovascular conditions earlier and make even more informed care path decisions. The first application is a stress test of cardiac and heart valve function without pharmaceutically or physical activity-induced stress. Other opportunity areas are complementary cardiovascular analyses and decision-support systems for cardiovascular diagnosis and therapy planning.
Team Cardio Prime consists of an interdisciplinary team of experts in cardiovascular disease diagnostics and treatments, physicists, engineers and software developers from Charité – Universitätsmedizin Berlin.
Prof. Dr. Titus Kühne, Kay Brosien
Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité – Universitätsmedizin Berlin
dentalXr.ai - Deep Learning for Dental Image Diagnostics
Dental diseases are among the most prevalent of mankind, burdening billions of individuals with pain, impaired chewing movements, impaired speech and aesthetics. To manage these diseases, early detection and regular monitoring with supportive therapy is needed. While visual-tactile detection has low sensitivity for early disease stages, the analysis of dental images is challenging due to limited accuracy of individual examiners, low consistency between examiners, and required time.
Team DentalXr.AI is developing an artificial intelligence (AI)-based decision-support system for dental images, intended to help dentists to systematically and comprehensively assess X-rays, document these assessments, and form evidence-based decisions. The envisioned solution enables faster and more accurate assessments of dental X-rays. This will result in reduced diagnostic uncertainty and better treatment decisions in less time. DentalXr. AI reduces assessment and treatment costs for patients and the healthcare system and makes dentists’ lives easier. Future application areas include incorporating additional image types and predictive capabilities.
Team DentalXr.AI consists of senior clinicians, machine learning experts and software developers from Charité – Universitätsmedizin Berlin.
PD Dr. Falk Schwendicke, Dr. rer. nat. Joachim Krois
Dept. of Restorative and Preventive Dentistry, Charité – Universitätsmedizin Berlin
"The DHA wa a great opportunity for us. It not only allowed us to develop a strong team using the flexible financial support provided, but to grow into a start-up, building the mindset and the network. We would not have reached the point where we are now without this support. We can highly recommend the program!"
LingPed - An Innovative Monitoring Platform for Post-Surgical Rehabilitation
Today, the rehabilitation of patients after surgery of the lower extremity is mostly a black-box to the surgeon. The responsibility to control the loading of the operated extremity and to move in a safe manner rests with the patient. This can be overwhelming and complex for patients. Failure to adhere to the postoperative protocol leads to an increase of complications, re-operations, socioeconomic costs and can negatively affect the quality of patients’ lives.
Team LingPed is closing this gap in post-surgical rehabilitation with a monitoring system for patients after orthopedic surgery of the lower extremities. The system consists of an insole for use e.g. in postoperative shoes (orthoses) for data collection, and an app for patients as feedback mechanism to monitor and, if needed, adjust their behavior during recovery. The solution will also assist the surgeon in planning an individualized rehabilitation protocol. The system intends to reduce the risk of re-surgery, shorten and optimize the individual rehabilitation process, and reduce healthcare system costs. Future application areas include pattern recognition of gait abnormalities, telemedicine, prognosis and prevention of foot deformities for children and teenagers for optimal foot development.
Team LingPed consists of orthopedic trauma surgeons of the Center for Musculoskeletal Surgery from Charité – Universitätsmedizin Berlin and a medical student with hardware and development software expertise.
Dr. med. Serafeim Tsitsilonis, Nevda Kaya
Center for Musculoskeletal Surgery, Charité – Universitätsmedizin Berlin
mTOMADY - A Transaction Platform for Accessible and Affordable Healthcare
More than 1 billion people in low- and middle-income countries lack access to basic healthcare. The majority of affected people do not have access to savings mechanisms and are at risk for unexpected expenses and even medical impoverishment. Recognizing this and related needs, promoting good health and well-being and alleviating poverty are UN Sustainable Development Goals.
Leveraging the global mobile phone infrastructure, team mTOMADY has developed a digital health wallet – a mobile transaction platform for healthcare savings. Healthcare sponsors, e.g., international aid organizations, governments, employers and communities, can contribute to individuals’ healthcare accounts, which in turn can only be used at accredited clinics within defined reimbursement ranges. This solution promises reduced “leakage” of aid funding by international aid organizations, quality improvement and cost-control for governments and healthcare providers, and – most importantly – increased access to affordable, quality healthcare for patients. mTOMADY is currently live with a pilot in Antananarivo in cooperation with the Government of Madagascar.
Team mTOMADY consists of two neurologists from Charité – Universitätsmedizin Berlin and a team of mobile technology, software development, and public health experts.
Dr. med. Julius Emmrich, Dr. med. Samuel Knauss
Dept. of Neurology with Experimental Neurology, Charité – Universitätsmedizin Berlin
"The flexibility and willingness of the DHA to adapt to the needs and requirements of each individual team is the great strength of this program. It is no one-size-fits-all approach but each team receives the support required to take the next step towards application."
MonICU: Artificial Intelligence-based Prediction of Complications in Intensive Care Units
Alexander Meyer is a computer scientist and senior resident in cardiovascular surgery. He is head of the research group “Data science in cardiovascular medicine” at the Department of Cardiothoracic and Vascular Surgery at the German Heart Center Berlin (Deutsches Herzzentrum Berlin). His main research interest is to improve patient safety with the application of state-of-the-art data science methodology in the medical domain.
Dr. med. Alexander Meyer
German Heart Center Berlin
"Networking and exchange of opinions, targeted coaching and sound mentoring: The Digital Health Accelerator Program from Berlin Health Innovations is for us a genuine 'worry-free package' for successful translation!"
PREDICTioN 2020 - Simulation-based AI for the Prediction of Stroke
Team PREDICTioN 2020 develops a simulation program for stroke prognosis with the aim of enabling optimal treatment strategies for stroke prevention.
Each year more than 1.2 million people suffer from stroke in Europe alone. 15% of which have a re-stroke within a year. Prevention strategies and clinical treatment of stroke are based on generalized guidelines and empirical data alone. No personalized diagnostics and treatment strategies are available. Digital opportunities are not exploited sufficiently. With this AI solution Team PREDICTioN 2020 aims at saving lives of stroke patients by personalizing stroke prevention and treatment utilizing high-precision imaging and unique Machine Learning approaches.
The innovative simulation model enables predictive diagnostics in stroke treatment using digital medical imaging. Patient-specific MRI and CT images are processed with state-of-the art processing-tools and convolutional neural nets. This information is fed to the team's unique simulation that allows the estimation of cerebral perfusion changes under different conditions.
The simulation results together with routine clinical data allow predictive modelling for stroke risk and outcome using innovative machine learning techniques. The approach will lead to personalized simulation of therapy options in stroke enabling patient-centered treatment and personalized risk assessment.
Team PREDICTion 2020 consists of neurosurgeon Dr. Dietmar Frey from Charité - Universitätsmedizin Berlin and a team of software developers, machine learning experts and scientific coordinators.
Dr. Dietmar Frey
Dept. of Neurosurgery, Charité – Universitätsmedizin Berlin
"DHA provided great support in going the next steps. By setting a common goal - the demo day - the whole team focused and put its effort behind our mission: Predicting stroke risk with artificial intelligence - to save lives! This included aligning the development of the product with the user, analyzing the market, developing a comprehensive business strategy and pitch training. In particular, the extensive and high-quality network enabled us to get feedback from different perspectives. Taken together, the DHA supported us getting on a new level."