IntoMed.AI Starter Pack
2024–2025 IntoMed.AI Starter Pack
Current Research Papers & Official Guidelines
Clinical Implementation
• Nature (2024): “Impact of human and artificial intelligence collaboration on workload”
Key Finding: Demonstrates a 27.2% time savings in medical imaging interpretation. [3]
• FDA’s 2024 AI Council
Key Initiative: New regulatory framework for AI in drug development, focusing on transparent evaluation metrics and risk mitigation. [5]
Drug Discovery
• MSU’s TopoFormer Research (June 2024):
Focus: A novel AI program accelerating drug development by automating complex molecular simulations. [4]
• Yale International Conference (July 2024):
Topic: AI applications in pharmaceutical research, including predictive modeling for early-stage drug candidates. [9]
Clinical Decision Support
• 2024 Comprehensive Review of AI-driven CDSS:
Publication: In-depth overview of Clinical Decision Support Systems leveraging machine learning and real-time data. [7]
• Nature (2024): “Reproducible AI Pipelines in Radiology”
Key Insight: Highlights the use of cloud infrastructure to ensure consistent, scalable analysis of radiological data. [8]
Regulatory Updates
• FDA’s March 2024 Guidance:
Document: Predetermined Change Control Plans for AI-enabled devices, offering structured pathways for iterative updates. [10]
• WHO’s 2024–2025 Strategic Approach:
Objective: Harness AI for global health equity, outlining governance frameworks and ethical best practices. [2]
Citations
1. FIU Business
2. WHO: Harnessing Artificial Intelligence for Health
3. Nature (2024): Impact of AI Collaboration on Workload
4. MSU News (June 2024): Transforming Drug Discovery with AI
5. FDA: AI in Drug Development
6. Yale Medicine: NLP in Biomedicine
7. PubMed (2024): AI-Driven CDSS Review
8. Nature (2024): Reproducible AI Pipelines in Radiology
9. Yale Medicine: AI in Drug Discovery Workshop
10. FDA Guidance (2024): Predetermined Change Control Plans
Google NotebookLM:
