AI Medical Compendium Journal:
Science advances

Showing 51 to 60 of 116 articles

Emergence and reconfiguration of modular structure for artificial neural networks during continual familiarity detection.

Science advances
Advances in artificial intelligence enable neural networks to learn a wide variety of tasks, yet our understanding of the learning dynamics of these networks remains limited. Here, we study the temporal dynamics during learning of Hebbian feedforward...

Quantitative softness and texture bimodal haptic sensors for robotic clinical feature identification and intelligent picking.

Science advances
Replicating human somatosensory networks in robots is crucial for dexterous manipulation, ensuring the appropriate grasping force for objects of varying softness and textures. Despite advances in artificial haptic sensing for object recognition, accu...

Trait-mediated speciation and human-driven extinctions in proboscideans revealed by unsupervised Bayesian neural networks.

Science advances
Species life-history traits, paleoenvironment, and biotic interactions likely influence speciation and extinction rates, affecting species richness over time. Birth-death models inferring the impact of these factors typically assume monotonic relatio...

Inductive biases of neural network modularity in spatial navigation.

Science advances
The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architect...

Generative AI enhances individual creativity but reduces the collective diversity of novel content.

Science advances
Creativity is core to being human. Generative artificial intelligence (AI)-including powerful large language models (LLMs)-holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on generative AI ideas. We st...

Toward human-like adaptability in robotics through a retention-engineered synaptic control system.

Science advances
Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to adapt or evolve in response to external experiences. To address this limitation, we propose an innovative approach that uses parallel-processable reten...

Discovering the gene-brain-behavior link in autism via generative machine learning.

Science advances
Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first approach could transform understanding and treatment of autism. However, isolating the gene-brain-behavior relationship from confounding sources of variab...

Autonomous assembly and disassembly of gliding molecular robots regulated by a DNA-based molecular controller.

Science advances
In recent years, there has been a growing interest in engineering dynamic and autonomous systems with robotic functionalities using biomolecules. Specifically, the ability of molecular motors to convert chemical energy to mechanical forces and the pr...

Particle uptake in cancer cells can predict malignancy and drug resistance using machine learning.

Science advances
Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools, capable of classifying cancer cells based on their functions, may substantially enhance therapy and extend patient life span. The connection between cell...

Machine learning-enhanced molecular network reveals global exposure to hundreds of unknown PFAS.

Science advances
Unknown forever chemicals like per- and polyfluoroalkyl substances (PFASs) are difficult to identify. Current platforms designed for metabolites and natural products cannot capture the diverse structural characteristics of PFAS. Here, we report an au...