Harnessing AI for STI Care: Image Recognition and Chatbot Innovation

Join us for an interactive workshop exploring cutting-edge applications of artificial intelligence in sexual health. This session will showcase how AI-powered image recognition is revolutionising the diagnosis of skin and mucosal lesions, and demonstrate the construction of a large language model–driven chatbot designed to provide accessible, expert-level STI counselling. Attendees will gain hands-on insights into the development, deployment, and clinical integration of these technologies, with a focus on improving care delivery across diverse global settings.

Background

Medical Artificial Intelligence (AI) is rapidly reshaping the landscape of infectious disease prevention and care, offering innovative tools for risk prediction, decision support, and diagnostic enhancement. This practical one-day workshop will introduce the fundamentals of medical AI with a focus on sexually transmitted infections (STIs). Participants will explore how radiomics techniques can be used to develop image-based screening tools for STIs, such as syphilis, gonorrhoea, and chlamydia, for early detection and build large language model–based chatbots for delivering personalised STI education and triage. Designed for beginners, the workshop assumes no prior knowledge of AI and combines foundational theory with hands-on practice. Attendees will gain step-by-step experience in setting up investigative projects based on simple AI models using text and image datasets, emphasising real-world clinical applications.

Workshop Instructors

Professor Lei Zhang is a health economist and medical AI expert who leads the development of AI tools for STI prevention and control. He pioneered machine learning models for predicting HIV and STI risk among men who have sex with men (MSM) in Australia, and continues to innovate AI-driven approaches to improve access and accuracy in sexual health services.

Jiajun Sun is a PhD candidate at Monash University and an expert in medical AI and image recognition. His research applies advanced radiomics techniques to identify and classify STI-related lesions, with applications extending into dermatology. His work demonstrates the power of AI to support clinical diagnosis through high-resolution image analysis.

Location: Plaza Heisei, 2-chōme-2-1 Aomi, Koto City, Tokyo 135-0064, Japan

Date: June 11, 2025

Registration link:https://forms.gle/41R5NaTJhBPVmAYFA (Registration will be closed on May 11, 2025)