Authors: David Josef Herzog, Nitsa Judith Herzog

Published on: April 01, 2024

Impact Score: 7.6

Arxiv code: Arxiv:2404.01403

Summary

• What is new: The paper highlights the unique challenges and opportunities presented by the Industrial Revolution 4.0 in healthcare, discussing the need for more explainable AI and the exploration of LLM in medical diagnostics.
• Why this is important: The exponential growth in data from various sources in healthcare has created a complex environment, making it difficult to meet the professional, social, and legal standards for medical diagnostics.
• What the research proposes: Proposes a multifaceted approach to improving AI’s explainability in medical applications and explores the potential and limitations of Large Language Models (LLM) in diagnostics.
• Results: Lists significant issues related to data management in healthcare and proposes comprehensive methods for addressing these challenges.

Technical Details

Technological frameworks used: Explainable AI, Large Language Models

Models used: Diagnostic Decision Support Software models

Data used: Heterogeneous healthcare data including imaging and patient data

Potential Impact

Healthcare industries, medical diagnostics companies, AI technology developers, and healthcare data management companies

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