Skripsi / TA of Muhammad Faisal Amir - Telkom University 2021

Consumer desktop from nutrition-framework API

A multimodal framework integrating VQA, Graph-Attentive Ingredient Embeddings (GAIE), and attention mechanisms to predict ingredient masses and nutritional values from overhead food images.

Abstract: Chronic diseases have affected many people globally and causing morbidity, and modality—the impact of chronic disease related to people’s lifestyles and their choices of habits like food, among others. Also, a model that immune and improves patients' lifestyle and habits by giving guidance and follow-up for future symptoms. As seen that there is high demand for specialists/experts in that field. Only a few studies have considered reducing the workload and exhaustion of physicians during the treatment phase. This article aims to provide a preliminary assessment of the Chatbot health system, a conversational agent-assisted health guiding framework to help doctors cope with burnout and provide continuous treatment to their patients. The approach is taken to create the chatbot dialog, and the guiding system is presented in this paper. As a result, talk about the first patient profiling technique for classifying patients based on their cholesterol levels. The machine then makes recommendations to the expert on tasks to include in the patient’s guidance in dialogue. This study makes three significant contributions to disease complications prevention (i.e., preserving a healthier lifestyle): (1) It provides the specialist/expert with a conversational agent to support patients; (2) It reduces experts’/specialists’ workload and safe their time to improves patient care by categorizing patients into groups, each group has its case scenario, that would help to follow up with patients until he visits a clinic/hospital for drugs or meeting doctors face-to-face; and (3) It gives the physician physical/nutrition activity guidelines when creating a general patient activity guiding choices based on his cholesterol level whether its normal, abnormal, or risk.

This project is a Recipe Recommendation System that suggests recipes tailored to the user's specified nutritional values and ingredients. It integrates machine learning techniques with an intuitive web application framework to provide personalized recipe suggestions.

The Calorie Tracker is a comprehensive Windows Forms Application (WFA) designed to help users monitor and manage their daily caloric intake. Built on the powerful foundation of Entity Framework Core, this application provides a seamless and intuitive interface for tracking nutrition.

A REST API to be consumed by nutrition-care-client project. Build on top of Laravel Framework

A Node REST API to be consumed by nutrition-care-client project. Build on top of Loopback framework.

FoodKG is a bilingual (Chinese–English) dataset and code framework designed to construct a comprehensive knowledge graph for forest foods and their nutritional attributes.

This iOS app allows users to track their health metrics using Apple's HealthKit framework and retrieve nutritional information for specified foods using an external API.

FitnessKing is a Magento Module ( Magento is a Zend Framework Project ) for Fitness, Nutrition, Gym, and Workout Management. The focus of FitnessKing is Security, Swiftness, and Scalability (S3)

MenuTracker is a database that contains nutritional information of menu items served by large out-of-home chains in the UK. Large chain restaurants are defined as those with over 250 employees that provide nutritional information on their websites. The codebase of MenuTracker is written in Python, predominantly using Scrapy framework.

A fitness tracker for Android written with Dart using the Flutter framework. FitSage uses Google ML Kit for text recognition to scan Nutritions Facts labels, and a SQLite database to store relevant information.

Nutrition API remade using PHP Slim framework

Pet management app (healh, nutrition, care, etc) made with Quasar Framework and MEVN stack

using framework CareKit to tract and analyses daily nutrition intake for patients after bariatric operation

Nutrition Web App Made using Golang (GIN and GORN frameworks), REACT frontend and PostreSQL database

this is a nutrition adviser that advises you what food to take based on your health condition. the nutrition adviser is made using scikit learn and django web framework

API REST for consulting nutritional information about food and meals and create dishes. Made in Django Rest Framework

An intelligent health and dietary assistant system based on LangChain framework and large language models. Features include food recognition, nutrition analysis, personalized health advice, and knowledge graph integration.

Framework for comprehensive variant detection in whole genome sequences using advanced machine learning models for cross domain pattern recognition in fitness, pharmacogenetics and nutritional aspects of sprint running

xTurnER is the Experience by Dakota Turner Evolution Regiments A comprehensive React-based web application for the Dakota Turner Hybrid Athlete Method, showcasing fitness guides, nutrition frameworks, and community engagement.

The Recipe Creator API, built with Django REST Framework, generates AI-powered recipes, supports dietary preferences, calculates nutritional info, and scales ingredients, with endpoints for listing, retrieving, and creating recipes.

AI-powered iOS Health Companion leveraging Apple Intelligence frameworks. Provides personalized nutrition insights, barcode-based food analysis, and dynamically generates custom meal plans based on user-specific health metrics. Awarded 2nd Place @ Confluentia Hackathon (IIT BHU).

Heartbeat is a logistics and data management web application using Python and the Django framework being built for an international charity that provides hope and healing to orphaned and vulnerable children, and their underserved communities, through its education, nutrition, medical, and foster care programs.

It is an effort to implement the Page Object Model (POM) To test the website using Selenium. I used Integrative Nutrition Inc's website in this project. I applied all the best practices of the POM framework to achieve a fluent interface and keep the project as user-friendly and easy-to-understand as possible.

The requirement of the project, an application that uses RESTful web services to provide useful functionality to end users. My Implementations, a desktop application named "Yummy Recipes" that uses RESTful APIs to acquire the recipe for any meal user provides. Python was chosen as the programming language for this app, along with Pyqt5 as a Python GUI framework. The used API (rapidapi.com/spoonacular/api/recipe-food-nutrition/)

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Official implementation of the framework for the paper: "Data-Augmented Machine Learning Validates Personalized Carbohydrate-Protein Supplement for Endurance Exercisers".

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