AI · Clinical Decision Support · Novel Medical Devices · Telemedicine
an ecosystem with integrated clinical decision support tools, artificial intelligence applications, novel medical devices and telemedcine capabilities for use in austere environments with limited resources
Learn moreCritical care and trauma management requires significant expertise and special diagnostic and therapeutic devices. Critical care is a data intense speciality where multi-attribute decision making is the key for therapeutic decisions, which are taken under stress and time-pressure. This makes management of critically ill patient prone to error, even for an experienced intensivist. In extraordinary situations and austere environments this problem is pronounced.
In all situations the major problem is the lack of experienced medical staff. We aim to solve this problem by developing an ecosystem composed of clinical decision support tools, artificial intelligence applications and novel medical devices.
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In disasters and pandemics number of critically injured/ill patients increases suddenly and logarithmically. This increase is out of proportion compared to available resources. Mobilization of additional resources is often delayed and insufficient.
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Military conflicts and combat situations require special expertise and equipment. Nature of combat may delay evacuation and advanced care of the critically injured. Within the context of modern combat, the troops need to be self sufficient in advanced care of the injured soldier. Harptek Ecosystem aims to ensure efficient advanced care of the wounded at as early as tactical field care (TFC), and tactical evacuation care (TEC) stages of TCCC.
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International military conflicts and potential food and water shortages make refugee crises a real threat for all countries. Large scale refugee crises is a major health care crises where patients are treated with limited resources. Humanitarian missions also will benefit from our solutions.
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Space missions and polar expeditions bring additional problems like care of patient in zero gravity and within a significantly limited area, in an environment exposed to solar radiation. This requires design and development of special equipment that can operate reliably in zero gravity and robust against the EMF imposed by solar radiation. The major problem is limitations in number of experienced medical staff recruited in these missions.
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Increasing costs of treatment and limitations in staffing imposes a new health care crises for many countries. Even the highly industrialized nations are prone to suffer from the effects of this crises. Many of our solutions are effectively applicable to solve these problems.
We clearly know the problem and its nature.
Prof. Kılıç, founder and main researcher of Harptek, is an experienced surgeon and critical care specialist, who has significant experience in disasters. His almost 30 years long journey is the basis of our vision. During this journey he had gained significant knowledge and experience on many disciplines of engineering. This enables us to view the problems from both medical and engineering perspectives at the same time. Being able to recognize the extent of the problem and limitations of the potential solutions is one of the major aspects that makes our team unique.
We know and respect the complexity and adaptive nature of the problems we face with. Despite the common tendency to use the most advanced algorithms for decision support and artificial intelligence solutions, most of them are not reliably applicable to problem solving in medicine. We select the most appropriate AI algorithm for the specific problem, because there is no one size fits all solution applicable to all problems. These include neural networks, fuzzy logic, expert systems, deep learning and combinations of these as appropriate.
Our ultimate goal is to develop completely autonomous medical devices for patient care, which are robust and reliable. This goal requires a clear understanding of clinical problems, treatment algorithms and response to treatment. Believing to be able to solve clinical problems by simply feeding a deep learning algorithm with data is an illusion. Disease states and treatment processes are complex adaptive systems and medicine is an art.
Our short term goal is to develop a reliable and robust ecosystem for care of critically injured/ill patients in austere environments with limited resources, both in respect to medical devices and experienced personnel.
The primary problems that we are working on are