AI Medical Compendium Journal:
Proceedings of the National Academy of Sciences of the United States of America

Showing 61 to 70 of 332 articles

A framework for quantifying individual and collective common sense.

Proceedings of the National Academy of Sciences of the United States of America
The notion of common sense is invoked so frequently in contexts as diverse as everyday conversation, political debates, and evaluations of artificial intelligence that its meaning might be surmised to be unproblematic. Surprisingly, however, neither ...

MEnTaT: A machine-learning approach for the identification of mutations to increase protein stability.

Proceedings of the National Academy of Sciences of the United States of America
Enhancing protein thermal stability is important for biomedical and industrial applications as well as in the research laboratory. Here, we describe a simple machine-learning method which identifies amino acid substitutions that contribute to thermal...

In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models.

Proceedings of the National Academy of Sciences of the United States of America
There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein...

Beyond spiking networks: The computational advantages of dendritic amplification and input segregation.

Proceedings of the National Academy of Sciences of the United States of America
The brain can efficiently learn a wide range of tasks, motivating the search for biologically inspired learning rules for improving current artificial intelligence technology. Most biological models are composed of point neurons and cannot achieve st...

Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes.

Proceedings of the National Academy of Sciences of the United States of America
Microbiome engineering offers the potential to leverage microbial communities to improve outcomes in human health, agriculture, and climate. To translate this potential into reality, it is crucial to reliably predict community composition and functio...

Soft robotics informs how an early echinoderm moved.

Proceedings of the National Academy of Sciences of the United States of America
The transition from sessile suspension to active mobile detritus feeding in early echinoderms (c.a. 500 Mya) required sophisticated locomotion strategies. However, understanding locomotion adopted by extinct animals in the absence of trace fossils an...

Deciphering RNA splicing logic with interpretable machine learning.

Proceedings of the National Academy of Sciences of the United States of America
Machine learning methods, particularly neural networks trained on large datasets, are transforming how scientists approach scientific discovery and experimental design. However, current state-of-the-art neural networks are limited by their uninterpre...

Interpretable algorithmic forensics.

Proceedings of the National Academy of Sciences of the United States of America
One of the most troubling trends in criminal investigations is the growing use of "black box" technology, in which law enforcement rely on artificial intelligence (AI) models or algorithms that are either too complex for people to understand or they ...

Brain-inspired neural circuit evolution for spiking neural networks.

Proceedings of the National Academy of Sciences of the United States of America
In biological neural systems, different neurons are capable of self-organizing to form different neural circuits for achieving a variety of cognitive functions. However, the current design paradigm of spiking neural networks is based on structures de...

A synergistic future for AI and ecology.

Proceedings of the National Academy of Sciences of the United States of America
Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in comp...