In order to develop an accurate automatic differential diagnostic system with statistical methods, a large amount of data from patient interviews is required. On the other hand, many Internet users often supply their own information to the public.Our hypothesis is that the medical data collected from general Internet users is useful to develop an automatic statistical diagnostic system. The purpose of this study is to assess this hypothesis.We installed a simple health information website on the Internet. On this website, we hosted a Web application that can infer diseases compatible with the information entered by the users. On this site, if its users had visited a medical institution after using this Web application, we requested them to inform us about doctors’ diagnoses. We developed an automatic diagnostic system based on the Naive-Bayes algorithm with only these data. For evaluation, we used as test data the cases from clinical case questions in a Japanese National Medical Practitioners Qualifying Examination, which medical students must pass to become medical doctors in Japan. We evaluated the correctanswer rate to prove whether this new application makes the minimum satisfactory judgment demanded of doctors. We collected 8812 cases from our website and developed an automatic diagnostic system based on the Naive-Bayes algorithm with these data. The correct-answer rate of this new application was 69.4% (95% CI, 58.8-80.1%). This rate is higher than the borderline (66%) of the examination.This result suggests that medical data collected from general Internet users is valuable in developing an automatic differential diagnostic system and that an online automatic diagnostic system can be developed that improves its own accuracy with user log data.