Black-Box Data: A new paradigm for biomedicine in the AI era

Luca Naef; Michael Bronstein

doi:10.1039/d6sc01189f

January 1, 2026Chemical ScienceOpen Access

Black-Box Data: A new paradigm for biomedicine in the AI era

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Key Points

The aim is to explore how AI is transforming biomedicine from traditional models to advanced methodologies.
Examine the transition from white-box to black-box models
Analyze the implications of AI in biomedical research
Identify key challenges and benefits of adopting new data paradigms
AI enhances the ability to analyze complex biomedical data
Black-box models can provide insights not easily attainable with traditional methods
The shift towards AI requires careful consideration of data transparency and ethics

Implication

This analysis demonstrates a paradigm shift in biomedicine, highlighting the role of AI in scientific discovery.

Abstract

As Artificial Intelligence cements its role as a cornerstone of scientific discovery, the field is undergoing a fundamental shift beyond the current transition from "white-box" first-principles models to "black-box" deep...

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Cite This Study

Naef et al. (2026) studied this question.

synapsesocial.com/papers/69d8958f6c1944d70ce069fa https://doi.org/10.1039/d6sc01189f

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Black-Box Data: A new paradigm for biomedicine in the AI era

Key Points

Implication

Abstract

Discussion

Cite This Study

Black-Box Data: A new paradigm for biomedicine in the AI era

Key Points

Implication

Abstract

Discussion

Cite This Study

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