Client Background

Client: A leading health-tech firm in the USA

Industry Type: Healthcare

Products & Services: Medical solutions, healthcare

Organization Size: 100+

The Problem

  • The problem is to efficiently create orthopedic case reports by extracting data from online sources, including articles, videos, and user comments.
  • It involves summarizing and citing relevant articles from PubMed.gov for the past 5 years related to the case.
  • This requires automating the extraction and summarization of data from websites, making it a time-consuming task if done manually.

Our Solution

  • Develops a Python tool that accepts a website URL as input and generates a case report.
  • Integrates web scraping to extract data from websites.
  • Utilizes AI, such as ChatGPT, for creating summaries and responses.
  • Leverages PubMed for citing and summarizing recent articles.
  • Provides a web application for user-friendly access to these capabilities.

Solution Architecture

  • Utilizes web scraping techniques to gather data from trusted medical websites.
  • Combines web scraping with AI, including ChatGPT, for generating case reports and responding to queries.
  • Utilizes PubMed for retrieving and summarizing recent articles related to the case.
  • Deploys a web application for user interaction and input.

Deliverables

  • Project Github Source Code

Tech Stack

  • Tools used
    • ChatGPT
    • BeautifulSoup
    • Requests
  • Language/techniques used
    • Python
  • Models used
    • None
  • Skills used
    • Python
    • WebScraping
    • ChatGPT prompting
  • Databases used
    • None
  • Web Cloud Servers used
    • None

What are the technical Challenges Faced during Project Execution

  • Accurate and reliable web scraping from diverse medical websites.
  • Integration of AI components for text generation and summarization.
  • Efficient querying and retrieval of articles from PubMed.
  • Handling different data formats and structures from various online sources.
  • Developing a user-friendly web interface for input and interaction.

How the Technical Challenges were Solved

  • Extensive research and testing of web scraping techniques for medical websites.
  • Integration of AI models and libraries for text generation.
  • Utilization of PubMed API for article retrieval and summarization.
  • Custom data parsers for handling diverse data structures.
  • Collaboration with medical experts for user interface design and feedback.

Summarize

Summarized: https://blackcoffer.com/

This project was done by the Blackcoffer Team, a Global IT Consulting firm.

Contact Details

This solution was designed and developed by Blackcoffer Team
Here are my contact details:
Firm Name: Blackcoffer Pvt. Ltd.
Firm Website: www.blackcoffer.com
Firm Address: 4/2, E-Extension, Shaym Vihar Phase 1, New Delhi 110043
Email: ajay@blackcoffer.com
Skype: asbidyarthy
WhatsApp: +91 9717367468
Telegram: @asbidyarthy

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