iDoctor Artificial intelligence disease recognition based on fundus image. Team members: Ke Wang Pengwei Li Mengting Du Chuanzan Wang

Goals for next week Aspects that are still not clear 1. How to acquire fundus images using existing devices? 2. What do the diabetics care about and how often do they go to hospital to exam their eyes? 3. What is the competitive factors of our product compared with others? Goals for next week 1. User research and market research 2. Design the structure 1.0 of our hardware 3. Try to make the algorithm available for smartphone 4. Showing a clear ophthalmoscope.

Software development(By Robert) Timeline and milestones for next week Market research and interactive design(By Doris) Software development(By Robert) • Analysis the questions that diabetics care about and the frequency they exam their eyes • Analysis for competitive products • Design the fundamental functions of APP • Configurate the environment of bazel • Learn to use it to tansform the algorithm Optical system(By Lee) • 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 Structure design(By Chazz) • 3D designing 1.0 by Solidworks • Manufacting and assembling the model by 3D Printer • Testing principle of the equipment (If possible)

Unique Value Proposition Open Canvas Open Canvas Project: iDoctor Problem Solution Unique Value Proposition 1. Doctors need to have abundant experience in fundus diagnosis 1. Using machine learning to analyze fundus images and diseases Diabetic retinopathy diagnosis with an accessible and cheaper method 2. Handheld hardware or using mobile phone 2. The cost of fundus diagnosis is expensive Key Metrics User Profiles User Channels 1. Clear fundus images and identify some common diseases Diabetics in rural and developing areas Generalize the use of our product in small clinics and drugstores at the beginning of promotion 2. Price is relatively low compared to similar products Resources Required Contributor Profiles Contributor Channels 1. Expertises: Optics, Medical, Industrial design, Algorithm, IP 1. Students or someone else who have certain professional ability mentioned before 1. Recommended by friends or teachers 2. Some advice about the relative regulations or rules about medical system, especially AI related 2. Relevant websites 3. Machine learning training set(open source of fundus diseases' images) 3. Ask mentors and students in Geneva Summer School for help 4. IR CCD, lens, half mirror, light source, adjustable lens holder, diaphragm, 3D-printer device, AWS

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