Listen to this articleVoxelCloud is a startup focusing on medical artificial intelligence. Founded in 2015 in Los Angeles, VoxelCloud provides automated medical image analysis and clinical decision support services based on artificial intelligence and cloud computing technologies. The current program covers lung cancer, retinal diseases, and coronary heart disease. VoxelCloud also has offices in Shanghai and Suzhou in China. Below is our interview with Xiaowei Ding, CEO and co-founder of VoxelCloud:
Q: You’ve recently announced near $8M in Series A Round; could you tell us something more?
A: We are glad to announce that we have raised $8.0M in series A financing led by Sequoia Capital in May 2017. The fund raised in this round, on top of the $5.5M angel investment we received in September 2016, will be used to expand our programs to cover more clinical areas, establish further collaboration with leading medical institutions in China and in the US, pursue regulatory filings, and marketing. We are also rapidly expanding our team.
Q: What factors about your business led your investors to write the check?
A: I think there are many reasons. First of all, our investors are very positive about the potential of artificial intelligence in medicine. They think this industry is going to expand quickly in the flowing years.
Second, we have kept ahead in technology in this field in both China and US. Our team has strong research capabilities, and the investors found that after careful investigations. Also, we are a research-oriented startup and has developed stably over the last year.
Third, we have already achieved some commercial success and acquired paid users. We are working closely with leading hospitals in China and in the US, and we also have high potentials to apply our products to different clinical scenarios.
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Q: What is the story behind VoxelCloud, how did you start?
A: We started VoxelCloud in 2015 in Los Angles. I have been passionate about medical industry when I was a child because both my grandma and grandpa were doctors in a leading hospital in China. So after I finished my bachelor degree in computer science, I decided to apply my computer science background to medical industry. During my PhD research in the computer science lab at UCLA, I explored the possibilities that medicine could benefit from the development of computer sciences. Later on, I worked at Cedars-Sinai Medical Center as a research assistant, and at that time I finally found my way to make a difference in the industry. Then my long-time research on artificial intelligence in medicine has become my startup.
In my research, I found that before 2013, AI in medicine research programs have been limited by the amount of data, and there was no good machine-learning algorithms to apply those clinical data. Then I thought I could contribute to the industry with better models and better algorithms. Through deep learning theories, VoxelCloud could improve the efficiency of medical diagnose for medical practitioners, because the machines could help with analyzing medical images if you teach them how.
After one-year of investigation and survey, I co-founded VoxelCloud, a startup which aims at providing medical images analysis and diagnosis assistance for clinical practices. With artificial intelligence and cloud computing technologies, we could teach machines to understand medical data and boost a doctor’s efficiency and diagnostic confidence.
Q: What kind of solutions do you offer to your customers?
A: In brief, we provide automated medical image analysis services and clinical decision support services for clinical practitioners. Our premium algorithms offer more accurate, efficient, and accessible personalized medical image analysis.
Specially, our service will include at least three forms. First, we provide service directly to healthcare providers (such as hospitals, medical centers, etc.) through clinical workflow integrated cloud-computing solutions. Second, we partner with existing hardware and software vendors to provide AI service. Third, we build a platform to enable third party medical developers to develop their own applications much easier through our medical knowledge graph API. With this API, developers could work more efficiently because we have developed the basic algorithms and collected massive amount of anonymized training data from scratch. Further extension of our project will leverage heterogeneous data sources in synergy with the existing imaging data.
Currently, our program covers lung cancer, retinal diseases, coronary heart disease.
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Q: What makes your company unique in the market?
A: First, we have the access to vast amount of structured, labeled medical data through our collaboration with leading hospitals, which remains a considerable bottleneck in the industry for developing more accurate algorithms.
Second, our team has strong research background in AI and medicine, and they are experts in the industry. For example, our chief scientist, Demetri Terzopoulos is Chancellor’s Professor of Computer Science at UCLA, and he holds the rank of Distinguished Professor and directs the UCLA Computer Graphics & Vision Laboratory. He is also the fellow of top organizations including ACM and IEEE. Our vice president of R&D, Jiaming Liang is an associate Professor of Biomedical Informatics and Computer Science at Arizona State University. Me myself, is a research assistant professor in the UCLA Computer Science Department. 80% of our team are technology workers. We know our stuff.
Third, we work closely with clinical practitioners and leading institutes such as ASU, UCLA, NIH, etc. Even earlier in the product development process, clinical practitioners have been involved to guide our development. The collaboration makes sure our service can really solve clinical problems and satisfy clinical needs.
Our company is a balanced combination of research and commercial applications, which gives us a unique advantage in the market. I believe with our strong academic research background and large clinical data, we could understand the industry better and solve clinical problems that are necessary.
Q: What is your mission?
A: Our goal is to improve the lives of millions across the world through accurate, accessible and efficient medical analytics. We believe the medical diagnosis should be objective and equally accessible, even in small towns that medical resource is limited. With the help of newest computer technologies, we have the possibilities to revolute the traditional clinical workflows and empower physicians to make informed clinical decisions worldwide.
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