Standardize medical data

The advancements in AI (Artificial Intelligence) are changing our daily lives, including the healthcare system. However AI is only effective when we have clean data. Clean data means Structure Data, Contextualized Data and Annotated Data. Only trainable data (Trainable Knowledge, Trainable Data Sets) has value with AI. Actually, this work requires a lot of effort especially for medical data. At Deepcare, we study tools to get a standardized pipeline in data collection, extraction from raw data sources in daily medical treatment

AI in healthcare

AI is Deepcare's most important R&D activity. We look forward to applying AI to transform medical data into knowledge in medical Diagnostic and treatment. With the application mathematical models and algorithms in medical imaging diagnosis (Imaging Diagnostic), natural language processing in medical contexts, clinical data processing (EHR - Electronic Health Record) we would like bring smart medical services to every patient in according to patient health condition (Precision Healthcare Services). Follow our latest R&D at www.ailab.deepcare.io

Privacy and security

Privacy is indispensable and necessary in an open society in the digital age. Privacy is different from secret. Privacy means we don't want to share information with unrelated people, The secret is that people don't want anyone to know. Privacy is the right to choose information to reveal yourself to the world. Medical privacy is the right to keep information about personal health, the right to choose health information to share with doctor on demand. At Deepcare, we are working on new approaches to mine medical data by AI technology while ensuring the privacy of users' sharing of medical data. Federated Learning, Blockchain are potential technologies in finding solutions to ensure privacy in medical data.