OdontoRisk — Python-based medication and systemic-risk screening assistant for dental care

Hi everyone,

I would like to share OdontoRisk, a Python-based Streamlit application for medication and systemic-risk screening in dental care.

OdontoRisk was developed as a clinical decision-support prototype to help dental professionals organize patient medications, allergies, systemic conditions, lifestyle factors, and optional vital signs into structured alerts before dental treatment. The app also generates a PDF report for clinical documentation.

The project was built as a practical exercise in Python, Streamlit, rule-based clinical logic, multilingual interface design, local Windows deployment, and PDF report generation, with development support from Codex by OpenAI.

Main features

  • Streamlit-based interface.
  • Portuguese, English, and Spanish support.
  • Automatic initial language selection in the local Windows version.
  • Medication parsing with spelling-tolerant recognition.
  • Screening of medication and systemic-risk domains relevant to dental care.
  • Structured clinical alerts.
  • PDF report generation.
  • Public GitHub repository for study, adaptation, and further development.
  • Local Windows one-click version available through GitHub Releases.

Use case

The app is intended for dental pre-care screening, especially when the clinician needs to review medication-related risks, systemic conditions, allergies, altered vital signs, or situations in which medical documentation may be appropriate before dental treatment.

Safety boundary

OdontoRisk is not intended to replace clinical judgment, medical consultation, medication package inserts, drug labels, local guidelines, or professional responsibility. It is a technical, educational, and clinical-documentation support prototype.

Links

GitHub repository: GitHub - IsaacDGE/odontorisk: Evidence-aware medication and systemic-risk screening assistant for dental care. · GitHub

Streamlit app: OdontoRisk · Streamlit

Author: Isaac Daniel Gonzaga Estevão
LinkedIn: https://www.linkedin.com/in/isaac-daniel-g-9b6b4b225/

I would be glad to receive feedback from the Streamlit community, especially regarding interface structure, deployment, maintainability, and possible improvements in the app architecture.