Paper Title
Intelligent, Personalized Diet Plan Web Services Based on Ontological HL7 Health Screening Data

The advancement of medical technology greatly extends people’s lifespan. Therefore, as many people try to keep well and fit, healthy diet is becoming more and more important today. However, deficiencies, excesses and imbalances in a diet can produce negative impacts on health, which may lead to diseases. The most all-too-common diseases and symptoms can often be prevented or alleviated by better diet active living. Moreover, the majority of dietitians are health professionals and are trained to provide safe, evidence-based dietary advice and interventions such as limiting maximum calorie intake daily, avoiding certain types of food, etc. However, most of people who desire health conscious diet are still in uncertain situations regarding which ingredients or food should be avoided in the context of daily life. In this research, we developed an ontological, RESTful Diet-Aid web service based on health screening data of Health Level Seven International (HL7) to provide an intelligent, personalized Diet-Aid service, which can be accessed by using any Internet-enabled device. The Diet-Aid can generate a dietetic meal or filter out unsuitable food on site according to user’s health conditions assuming that the recipe information of food is accessible. The development of such a Diet-Aid is expected to benefit both institutions of health screening and food suppliers. Index Terms - Health screening; Diet plan; Health Level Seven International; Knowledge-based system; Ontology