Bone Age Assessment for Pediatric Patients
Python
PyTorch
Deep Learning
Computer Vision
Medical AI
This Master's thesis project involved developing an AI system for pediatric bone age assessment using deep learning techniques.
The system analyzes X-ray images of the hand and wrist to determine the developmental age of pediatric patients,
which is crucial for diagnosing growth disorders and monitoring treatment progress.
The project utilized convolutional neural networks with a custom architecture optimized for medical image analysis.
I implemented various preprocessing techniques specific to X-ray images and conducted extensive experiments to
improve accuracy and reliability. The final system achieves results comparable to human radiologists.
AI-based Assistance Tools and Chatbots
Python
FastAPI
Docker
MLOps
NLP
Developed highly scalable AI-based assistance tools and chatbots capable of handling up to 10,000 requests per second.
These systems were built with a microservices architecture and containerized using Docker for easy deployment and scaling.
The project involved creating robust API endpoints with FastAPI, implementing efficient database connections,
and setting up monitoring and logging systems. The chatbots were trained on custom datasets and optimized for
low-latency responses, making them suitable for high-traffic applications.
Custom Educational CMS
Python
Django
PostgreSQL
JavaScript
Built a powerful content management system for educational scheduling as part of my Bachelor's thesis.
This system focuses on class, student, and teacher management, providing a comprehensive solution for educational institutions.
The CMS includes features such as automated scheduling, conflict resolution, attendance tracking,
grade management, and reporting tools. The system was designed with a user-friendly interface to accommodate
users with varying levels of technical expertise.