About Webinar

This webinar focuses on what it actually takes to build and deploy a medical imaging AI system beyond the prototype stage. 

We walk through the full system, from dataset preparation and model development to integrating it into existing products. 

The session is designed for product teams and technical leaders who need to make AI systems work in real environments, not just in isolated experiments. You’ll learn how to go from a trained model to a system that can actually be deployed and used. 

We’ll cover:

• how to gather and structure datasets for long-term use and iteration
• experiments - choosing the adequate model and training it
• key architectural decisions when moving from model to system
• deploying the models 
• performance, failure handling, and monitoring in production
• integrating AI components into existing healthcare platforms

The content is based on real production experience from Sotex Solutions, including what tends to go wrong and what teams often underestimate when building medical AI systems.

Speakers 

Lazar Krstić is an AI Lead at Sotex Solutions and an AI engineer specializing in computer vision and real-world AI applications, particularly in healthcare. He focuses on building systems that turn complex visual data into practical, actionable insights. He began his career working on biomedical imaging projects, contributing to large-scale solutions in digital pathology, including tissue segmentation, tumor detection, and phenotype classification. His work has supported both production systems and scientific research.

In addition to his industry role, Lazar is the founder of ArchFix, a startup developing a smartphone-based solution for early detection of flatfoot in children. The platform combines computer vision with personalized guidance and progress tracking, aiming to make early diagnosis more accessible and engaging.

Mladen Stanojević is a highly accomplished Software Architect and CTO and CEO with over 15 years of experience leading technical teams and delivering complex, highly regulated enterprise solutions across Europe, Africa, and the USA. Holding an M.Sc. in Computer Sciences and Electrical Engineering from the University of Novi Sad, he has built a robust career designing systems that handle vast quantities of data, rigorous data analysis, and intricate integrations within the utility, medical, and financial sectors. Mladen's deep expertise in architecting high-performance validation engines, managing large-scale projects, and building structured data systems provides the exact foundational infrastructure knowledge required to successfully deploy, manage, and scale modern AI solutions, making his insights invaluable for today's discussion.