Friday, April 19, 2024

JAMA on Medical AI Accuracy; Stanford Releases 500-page report on AI 2024

JAMA releases an important short article, "Comparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions," by Han et al.  (here).  Authors from Berlin, Munich, Aachen.  See also a 9-minute podcast.  

AI performance across a variety of tests and AI models continues to improve, with some differences between models and subject areas.   Many models are competitive with, or exceed,  human performance.

The graphic below shows six models and 1 human group when graded on harder (left) and easier (right) questions.  In each cluster, the humans are on the right.   All answers get better performance with easier (right) questions, but gpt4V consistently outperforms humans (far left vs far right column in each cluster).  There are several other graphics in the article.

click to enlarge


Stanford releases its April 2024 500-page report on progess in AI.   See a news article about it here.

See the home page here.   Get the full PDF here.  Get the 32-page Science/Medicine chapter here.  See a summary of the Stanford report, by Margaretta Colangelo, here.

AI Corner

ChatGPT4 summarizes the Sci-Med chapter.

The chapter on Science and Medicine in the 2024 Artificial Intelligence Index Report highlights the significant advancements in AI's role within these fields, emphasizing both scientific discovery and medical innovations. Here's a detailed summary:

In 2023, AI's influence in scientific research led to substantial developments in various areas, from weather forecasting to materials science. One key highlight was the introduction of AlphaDev, an AI system that developed efficient sorting algorithms, marking significant progress over decades of manual research. Another noteworthy project, FlexiCubes, utilized AI for optimizing 3D mesh constructions, crucial for applications ranging from gaming to scientific visualization.

The medical field also saw remarkable AI-driven innovations. Systems like SynthSR have transformed brain scan analyses by synthesizing standard medical scans into high-resolution images, aiding in both research and clinical settings. Furthermore, AI's role in diagnosing and managing diseases has expanded, illustrated by the development of AI tools like EVEscape for pandemic prediction and the advanced mutation classification capabilities of AlphaMissense.

Moreover, AI models have been increasingly recognized by regulatory bodies such as the FDA, which approved a significant number of AI-related medical devices, underscoring their reliability and effectiveness. The chapter also delves into AI's potential to enhance healthcare administration and patient care, citing systems like MedAlign, which aims to reduce administrative burdens through AI-driven solutions.

Overall, the chapter provides a comprehensive look at how AI is reshaping the landscapes of science and medicine by accelerating research processes, enhancing diagnostic accuracy, and improving overall efficiency in healthcare operations.

Proteomics performance enhanced by AI interpretation of signals (Alz.)

Sidebar: 10 Key Takeaways

AlphaDev: AI system developed new efficient sorting algorithms, impacting computational research significantly.

FlexiCubes: AI-driven optimization of 3D mesh constructions, improving applications in diverse fields.

SynthSR: AI transformation of brain scans into high-resolution images, enhancing medical analysis.

EVEscape: AI tool for predicting pandemic patterns, aiding in preemptive healthcare strategies.

AlphaMissense: AI model for classifying genetic mutations, potentially revolutionizing genetic research.

FDA Approvals: Increased approval of AI medical devices, confirming their efficacy and safety.

GraphCast: Enhanced weather forecasting through AI, demonstrating superior accuracy.

GNoME: AI's breakthroughs in materials science, discovering new materials faster.

MedAlign: AI application in healthcare administration, aiming to streamline operations.

CoDoC: Integration of AI in clinical settings, optimizing diagnostic processes and outcomes.

[/end ChatGPT4]