Summary of Ai Driven Health Recommender, by K. Vignesh et al.
AI driven health recommender
by K. Vignesh, B. Pranavi, Ch. Sreenidhi
First submitted to arxiv on: 23 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a web-based application that utilizes machine learning (ML) to assist patients in managing their diseases. The system, built using Flask, takes patient-provided symptoms as input and generates personalized recommendations for medication, precautions, diet, and workouts. This integrated approach aims to minimize the disease’s impact. To develop this application, the authors leveraged ML as a foundation, utilizing clean and real-time data. Evaluation metrics, specific datasets, or task-specific benchmarks are not mentioned in the abstract. The system’s primary goal is to streamline patient care by providing relevant information and guidance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine having a personal doctor assistant on the internet! This paper explains how they built an app that helps people with diseases take better care of themselves. You can enter your symptoms, and the app will suggest medicines, precautions, food to eat, and exercises to do. The goal is to make it easier for patients to manage their illnesses and feel better. The app uses a special kind of computer science called machine learning to work its magic. |
Keywords
» Artificial intelligence » Machine learning
