The name of project is iDoctor.
It consists of three parts:
1. Low cost fundus camera
2. Limit resource AI algorithm
3. Business model: data driven Open virtuous cycle
Goal：Showing a clear ophthalmoscope
• Calculate the focal length of the lens used and distance between the lenses
• Try to use half mirror or hollow reflector
• Select the suitable light source
Goal：Design the structure 1.0 of our hardware
• 3D designing 1.0 by Solidworks
• Manufacting and assembling the model by 3D Printer
• Testing principle of the equipment (If possible)
Goal：Configurate the environment of bazel
• Configurate the environment of bazel
• Learn to use it to tansform the algorithm
Goal：User research and market research
• Analysis the questions that diabetics care about and the frequency they exam their eyes
• Analysis for competitive products
• Design the fundamental functions of APP
design the interface of application
1. take pictures using camera
2. obtain report after upload results
3. review past report
4. maintain the individual information
database: diabetic retinopathy detection-kaggle
This is the link to MedTech Hack
contact: Ranveig Strom <email@example.com>
iDoctor is committed to eliminating the imbalances in medical resources (in China) through diagnostic artificial intelligence (AI) technologies. Almost all of the AI medical services are faced with three major challenges at present: the shortage of qualified medical data, the lack of profitable business model and the accuracy of AI algorithm.
To tackle these challenges, we aim to build a medical screening device to be placed in local pharmacies for the diagnosis of certain identified diseases. At current stage, we are building an open source fundus camera for the diagnosis of diabetic retinopathy – a prevalent diabetes complication that cause blindness. We hope that the same model can be extended to more disease screenings, like cervical cancer, in the future.
Patients can use our diagnostic device and obtain a free diagnosis report if they agree to share their medical data anonymously. Otherwise patients can still use the device for diagnosis with a fee significantly lower than hospital.
Our data will be open source and made available to all medical researchers for the creation of a more accurate algorithm – benefiting the patients, especially for those living in resource-deprived areas.
iDoctor will generate profit from the diagnosis fees charged to the patients who do not wish to upload their data and the profit will be shared with the pharmacies and the companies who provide the diagnostic service by algorithm.
Ke WANG (Robert):
I have a bachelor's degree of biomedical engineering and I am studying for a master of data science. I have worked at a Chinese three A hospital before as an engineer of Endocrinology laboratory and an officer of medical device management. I have always been interested in the future business model of AI medical service.
I am studying for a master of Biomedical Engineering, my main research direction is Biomedical Optics, for example: diagnosis of cirrhosis of the liver. I also have some knowledge of Material Sciences and Engineering.
I am studying for a master of data science at Tsinghua university. My main research direction is Intellectual Property (IP) law, including the policy and strategy research. I obtained my undergraduate degree in E-commerce in China Agricultural university.
Chuanzan WANG (Chazz):
I have a background as Mechanical Engineering, and now studying on Data science in Tsinghua Univ. China as a Master student. In this program, I am designing and assembling the hardware of fundus observation device.