Development of Personalized Diet and Exercise Recommender System Based on Clinical Data

By: Vaishali, Sheshrao Vairale

The present health scenario indicates that thyroid diseases are a common

challenge experienced by most individuals. According to the statistics in India,

one out of eight women suffer from thyroid-related conditions. Hyperthyroid,

hypothyroid, or thyroid cancer are categories of thyroid disorder. It is imperative

to maintain optimum levels of secretion of the thyroid hormones as the imbalance

could lead to thyroid diseases. Therefore, thyroid patients must be vigilant

regarding their iodine intake and follow a customized daily diet and exercise plan.

The diet plan, along with balanced iodine levels, must also be able to meet the

patient's nutritional needs. A personalized diet plan could help thyroid patients to

be more aware and focused on their body metabolism. Existing recommender

systems usually provide generic diet recommendations, and unfortunately, it may

not be beneficial to patients suffering from a specific disease.

Content-based Neighborhood-Conditional RBM (CB-NCRBM) model has

posited to recommend Top-3 diet and exercise plans for thyroid patients. The

proposed model considers the joint probability distribution of different scores

using the user profile. Similarly, preference and health scores are estimated based

on content features. The model feeds these scores as visible units to conditional

RBM. The proposed model also integrates several content-based features such as

users' physiological profiles, thyroid disease information, food, and exercise

preferences. The proposed recommender model validates the experimental results

using recommendation error and classification accuracy metrics. The proposed

hybrid model outperforms several popularly used recommendation models, such

as collaborative filtering, content-based, and pure RBM models. The system also

provides a feedback loop to enhance the quality of the recommended diet and

exercise plans based on user experience.

• Format: Paperback
• Language: English
• ISBN: 9342244785
• ISBN13: 9789342244785
• Release Date: January 1
• Publisher: Asmtm
• Length: 100 Pages
• Weight: 0.32 lbs.
• Dimensions: 0.2" x 6.0" x 9.0"