Affiliation:
1. Cloud and IoT Research Lab, CSED Thapar Institute of Engineering and Technology Patiala Punjab India
Abstract
SummaryFood is one of the most underrated entities with respect to diseases. Food or Diet plays a vital role in healing or recovery of a patient which brings forth the need of analyzing disease and diets associations. The study of such associations is crucial for recommending appropriate diets to patients but is an arduous task due to the complex interdependencies as is evident in literature. Thus, it becomes necessary to automate the analysis and make it available as a service. The main aim of this work is to efficiently collate and analyze disease‐diet associations and provide it as an accessible and adaptable service using a combination of advanced techniques. Complex disease‐diet interdependencies are curated from the literature and transformed into a network offering various parameters for further analysis. The analysis is done using machine learning algorithms to predict accurate and robust recommendations. Cloud computing aids this analysis by providing sufficient resources and making it more accessible. Thus, the recommendations are constructed using amalgamation of techniques including network analysis, machine learning, and cloud computing. The deduced associations from the analysis of medical data using these technologies would aid doctors and healthcare institutions in decision making thereby improving the prognosis of a disease.
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