DocDim/DetectX

Detect-X is a software solution designed to strengthen epidemiological surveillance. It assists healthcare professionals in the rapid identification of suspected cases for priority diseases, based on the official case definitions of the Cameroon's Integrated Disease Surveillance and Response (IDSR) technical guidelines. # Detect-X | Clinical Decision Support & IDSR Surveillance **Detect-X** is a software solution designed to strengthen epidemiological surveillance. It assists healthcare professionals in the rapid identification of suspected cases for priority diseases, based on the official case definitions of the Cameroon's **Integrated Disease Surveillance and Response (IDSR)** technical guidelines. ## 🌟 Key Features * **Weighted Clinical Analysis**: Calculation of a suspicion score based on the clinical importance of symptoms (Major signs vs. Minor signs). * **Comprehensive IDSR Database**: Covers 23 priority pathologies including Cholera, Hemorrhagic Fevers (Ebola, Marburg), Measles, and Poliomyelitis. * **Dynamic Dashboard**: Real-time visualization of statistical aggregates, critical alerts, and geographical distribution by health district. * **History Management**: Persistent archiving of consultations with advanced filters (Patient code, District, Date). * **Bulk Import**: CSV import module with a real-time progress bar for processing large patient cohorts. ## 🛠️ Project Architecture Based on the current system tree: ```text DETECTX/ ├── app/ │ ├── data/ │ │ ├── dict_patologies_weighted.json # Knowledge Base (Criteria & Weights) │ │ └── analyses_history.json # NoSQL Database of cases │ ├── services/ │ │ └── analysis_service.py # Business logic and stats calculations │ ├── templates/ │ │ ├── dashboard.html # Epidemiological tracking interface │ │ └── index.html # Individual diagnostic interface │ ├── engine.py # Rule engine for scoring │ ├── routes.py # REST API and workflow management │ └── models.py # Data structure definitions ├── static/ # CSS, JS, and Image resources ├── run.py # Flask application entry point ├── generate_test_data.py …