Should Artificial Intelligence Play a Durable Role in Biomedical Research and Practice?

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(24), P. 13371 - 13371

Published: Dec. 13, 2024

During the last decade, artificial intelligence (AI) was applied to nearly all domains of human activity, including scientific research. It is thus warranted ask whether AI thinking should be durably involved in biomedical This problem addressed by examining three complementary questions (i) What are major barriers currently met investigators? suggested that during 2 decades there a shift towards growing need elucidate complex systems, and this not sufficiently fulfilled previously successful methods such as theoretical modeling or computer simulation (ii) potential meet aforementioned need? it recent well-suited perform classification prediction tasks on multivariate possibly help data interpretation, provided their efficiency properly validated. (iii) Recent representative results obtained with machine learning suggest may comparable displayed operators. concluded play an important role practice. Also, already other physics, combining conventional might generate further progress new applications, involving heuristic interpretation.

Language: Английский

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A computational deep learning investigation of animacy perception in the human brain

Communications Biology, Journal Year: 2024, Volume and Issue: 7(1)

Published: Dec. 31, 2024

Abstract The functional organization of the human object vision pathway distinguishes between animate and inanimate objects. To understand animacy perception, we explore case zoomorphic objects resembling animals. While perception these as animal-like seems obvious to humans, such “Animal bias” is a striking discrepancy brain deep neural networks (DNNs). We computationally investigated potential origins this bias. successfully induced bias in DNNs trained explicitly with Alternative training schedules failed cause an Animal considered superordinate distinction classes, sensitivity for faces bodies, shape over texture, role ecologically valid categories, recurrent connections, language-informed visual processing. These findings provide computational support that unique property yet can be explained by learning history.

Language: Английский

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Why psychologists should embrace rather than abandon DNNs

Behavioral and Brain Sciences, Journal Year: 2023, Volume and Issue: 46

Published: Jan. 1, 2023

Deep neural networks (DNNs) are powerful computational models, which generate complex, high-level representations that were missing in previous models of human cognition. By studying these representations, psychologists can now gain new insights into the nature and origin vision, was not possible with traditional handcrafted models. Abandoning DNNs would be a huge oversight for psychological sciences.

Language: Английский

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Can an emerging field called ‘neural systems understanding’ explain the brain?

The Transmitter, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

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