About Workshop
This workshop on AI in Biomedical Research: A Hands-On Approach offers a deep dive into how AI is transforming modern medicine. Designed for students, professionals, and researchers, the program introduces core concepts of artificial intelligence and explores its practical applications across biomedical fields. Participants will begin by building a strong foundation in AI, machine learning, and deep learning with a special focus on their role in medical diagnostics.
As the workshop progresses, the focus shifts to the intersection of AI with drug discovery and personalized medicine. Topics include AI-driven target identification, genomic data analysis, and the integration of wearable technologies and virtual health assistants. Critical discussions on ethics, regulatory frameworks, and the societal impact of AI in healthcare will round out the experience, ensuring participants are equipped not just with technical skills, but also with a nuanced understanding of real-world challenges and responsibilities.
Aim
This workshop aims to introduce participants to foundational and advanced applications of AI in the biomedical sector. It provides practical exposure to AI-enabled diagnostic systems, drug discovery frameworks, and personalized healthcare tools. Participants will learn how intelligent algorithms are transforming disease detection, treatment customization, and medical research.
What Participants Will Learn
- Understand AI foundations in the biomedical domain
- Apply machine learning to healthcare datasets and imaging
- Explore AI-driven drug discovery processes
- Analyze how AI supports personalized healthcare decisions
- Recognize ethical and regulatory frameworks in medical AI
Structure
Session 1: AI in Biomedicine
- AI for Medical Imaging (X-ray, CT, MRI)
- Hands-On Tools: DxGPT
- AI in Predictive Medicine
- Ethical, Regulatory, and Societal Impacts
- Hands-On Tools: ParaView
Important Dates
Registration Ends
3:00 PM
Workshop Dates
2025-06-25
4:00 PM
4:00 PM
What You Will Gain
Outcomes
- AI applications in diagnostics and drug discovery
- Build and evaluate AI models for imaging and genomic data
- Develop critical thinking around ethical AI use in health
- Translate data insights into personalized care recommendations
- Enhance employability for interdisciplinary roles in biomedical AI
Who Should Attend
- Students pursuing or holding a degree in Biomedical Engineering, Biotechnology, Computer Science, Pharmacy, Bioinformatics, or related life sciences and technology fields.
- PhD Scholars and Researchers engaged in areas such as AI in healthcare, computational drug discovery, biomedical data science, genomics, or medical diagnostics.
- Industry Professionals from healthcare, pharmaceutical R&D, bioinformatics, medical imaging, diagnostics, and AI/ML sectors looking to enhance their interdisciplinary capabilities.
- Aspiring Learners with a keen interest in applying AI, machine learning, and digital technologies to solve real-world challenges in drug discovery, diagnostics, and personalized healthcare.