anamnesis.ai

anamnesis.ai

Project Description: AI-Driven Anamnesis Collection System

Overview

This project aims to develop an AI-driven anamnesis collection system in the healthcare domain. The system will leverage the capabilities of FHIR (Fast Healthcare Interoperability Resources), the ChatGPT API for collecting patient medical history (anamnesis) through conversational AI.

Technical Components

1. FHIR (Fast Healthcare Interoperability Resources):

   • Used for structuring, storing, and retrieving patient anamnesis data.
   • Ensures compliance with healthcare data standards.
   • Facilitates potential future integration with other healthcare systems.
   • BSD: https://github.com/nazrulworld/fhir.resources

2. ChatGPT API:

   • Powers the conversational AI interface.
   • Engages with the user to collect symptoms and medical history.
   • Intelligent and natural language processing capabilities enhance user experience and data collection accuracy.

3. Anamnesis Data Handling:

   • Responses from the user are processed and structured into FHIR-compliant formats, specifically using Observation resources to record each piece of anamnesis.
   • The data is then stored in the SQLite database, maintaining a record of the interaction and the medical information gathered.

4. Data Structure and Retrieval:

   • Each user interaction generates a series of FHIR Observation entities, capturing the essence of the patient's current health status and history.
   • These observations are linked to a mock Patient resource for the sake of the MVP, facilitating a structured and standardized anamnesis record.

Test Data

The test data was obtained from https://springernature.figshare.com/collections/A_dataset_of_simulated_patient-physician_medical_interviews_with_a_focus_on_respiratory_cases/5545842/1

Source: Smith, Christopher William; Fareez, Faiha; Parikh, Tishya; Wavell, Christopher; Shahab, Saba; Chevalier, Meghan; et al. (2022). A dataset of simulated patient-physician medical interviews with a focus on respiratory cases. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.5545842.v1

Conclusion

This project serves as a foundational step towards a more comprehensive AI-driven healthcare data collection system. By combining the latest in AI conversational technology with standardized healthcare data protocols, it aims to streamline the anamnesis process, thereby enhancing patient care and healthcare data management.