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This event offers a detailed, clinically oriented examination of the integration of artificial intelligence (AI) and machine learning (ML) into medical diagnostics and healthcare delivery. Designed as a practical resource for clinicians, researchers, and healthcare administrators, it systematically explores how AI technologies are being adopted, while critically addressing the challenges and opportunities presented by their real-world implementation.

A central focus of the event is its detailed exploration of the technical underpinnings of ML in medicine. It explores model evaluation, emphasizing the limitations of traditional metrics like accuracy, the importance of robust validation, and the need for comprehensive performance measures such as learning curves, confusion matrices, and external testing. Special attention is given to the evaluation of ML algorithms for image classification and to the selection of appropriate models for specific diagnostic tasks.

The event also introduces a standardized validation framework aligned with regulatory guidance, including clinically oriented composite utility metrics and protocols for ongoing model monitoring. It critically examines the impact of feature selection and data leakage through case studies, demonstrating how methodological pitfalls can lead to misleading claims of performance.

Recognizing the complexity of real-world deployment, the event provides practical tools and checklists for clinicians to appraise AI solutions, operational frameworks for safe integration, and guidance on governance and continuous learning.

By combining technical rigor with clinical relevance, the event empowers healthcare professionals to critically evaluate, safely integrate, and effectively leverage AI tools for improved patient outcomes. It serves as an essential resource for navigating the evolving landscape of AI-assisted medical diagnostics, supporting responsible and equitable innovation in healthcare.

This event is part of #AIWeekNY by Pulse NYC — a community-led festival celebrating innovation across the AI ecosystem. More at 

AI-Assisted Medical Diagnostics