Conference Scope and Objectives
The International Conference on AI in Medicine, Science & Technology (AIM-SciTech) aims to serve as a premier interdisciplinary forum for researchers, clinicians, scientists, industry professionals and policymakers to present and exchange cutting-edge research, innovations and best practices in Artificial Intelligence across Medicine, Science and Emerging Technologies. The conference will provide a platform for interdisciplinary exchange, showcasing AI applications in diverse domains such as Radiology and Advanced Medical Imaging, Healthcare Analytics and Clinical Decision support, Cyber Forensics, Drug Discovery and Design, Natural Language Processing (NLP), Large Language Models (LLMs), Knowledge Graph, Internet of Things (IoT), and Quantum Computing. 

AIM-SciTech also emphasizes responsible, explainable and trustworthy AI, addressing ethical, regulatory and societal aspects, while fostering strong collaboration between academia, healthcare organizations and industry to translate AI-driven research into real-world impact. With increasing adoption of AI in medical diagnostics, forensic case analysis and biomedical imaging, a dedicated international forum is vital to address challenges, share innovations and explore regulatory and ethical frameworks. The conference will bridge the gap between technologists and domain experts, driving collaborative innovations for real-world impact.

Conference Tracks

Track 1: AI in Medicine and Medical Imaging

• Predictive diagnostics and decision support

• AI in personalized medicine

• NLP for clinical data

• Deep learning in radiology and pathology

• AI in MRI/CT scan analysis

• Image reconstruction and segmentation

• AI in Forensic Odontology

Track 2: NeuroSymbolic AI & Knowledge Graphs 

• Explainable Medical AI\

• KG-Driven Imaging

• Neurosymbolic AI

Track 3: NLP and GenAI 

• Generative models: GANs, LLMs

• Applications of GenAI in Security, Healthcare and Media

• Prompt Engineering and finetuning of foundational models

• Retrieval Augmented Generation

• AI Agents and Frameworks

Track 4: AI in Computational Sciences 

• AI in MDS

• AI in Drug Discovery

• Quantum Biology Simulation

• Space, Quantum Computers

• Material Simulation