Academic Project | BUAP - Faculty of Computer Science

This project is a robust digital platform designed to optimize the management of the Ángeles Hospital Network (25 locations across Mexico).

Beyond simple appointment scheduling, this system implements Graph Theory and geospatial algorithms to solve logistical problems, such as finding the nearest hospital for a patient and calculating optimal routes between medical centers.

The core logic relies on advanced Data Structures and Algorithms:

• Modeled the 25 hospitals as Nodes and the routes as Edges.
• Developed a dynamic graph structure to represent the connectivity of the entire hospital network.

• Implemented Dijkstra’s Algorithm from scratch to calculate the most efficient route between hospitals.
• Allows the system to recommend optimal transfers based on real distance weights.

• Integration of the Haversine Formula to calculate real-world spherical distances between patients and hospitals using GPS coordinates (Latitude/Longitude).
• Automatically detects the nearest facility to the user's location.

• Processing and validation of complex datasets:
  • pacientes.csv (Patient records)
  • doctores.csv (Specialists and availability)
  • rutas_hospitales.csv (Network topology)
• Data cleaning module to handle missing coordinates and normalize hospital names.

The system is organized into functional modules for better maintainability:

├── datos/                      # Folder containing CSV Datasets
├── inicio.py                   # 🚀 Main execution entry point
├── hospital_cercano.py         # 🌍 Geospatial Logic (Haversine Formula)
├── rutas_hospitales_doctor.py  # 📍 Graph Logic & Route Optimization (Dijkstra)
├── agendar_cita.py             # Appointment scheduling logic
├── buscar_doctores.py          # Search & Filtering algorithms
├── login_paciente.py           # Patient Authentication
├── login_doctor.py             # Doctor Authentication
├── menu_paciente.py            # User Interface Navigation
├── ui_tema.py                  # UI/UX Theme configurations
└── utils.py                    # Helper functions for data loading

Developed by the Engineering Team at Benemérita Universidad Autónoma de Puebla (BUAP):

• Danna Patricia Riveroll Martínez
• Abraham Fuentes López
• Gabriela Nicolás Torres
• Lidia Gizem Sánchez Montiel