Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 30,201 to 30,210 of 220,100 articles

Generative design of intrinsically disordered proteins based on conditioned protein language models: Data is the limit

bioRxiv Apr 16, 2026
Intrinsically disordered proteins and regions (IDRs) are central to a multitude of biological processes. Despite extensive studies of their structural and physicochemical properties, the rational design of IDRs with defined conformational behavior re... read more 
bioinformatics

Neural mechanism of postural sway-related beta-band oscillations: a cortico-basal ganglia-thalamic network model of intermittent control

bioRxiv Apr 16, 2026
Recent EEG studies of human quiet stance have identified beta-band event-related desynchronization (beta-ERD) and synchronization (beta-ERS; post-movement beta rebound) during the micro-fall and micro-recovery phases of postural sway, respectively. T... read more 
neuroscience

Sampling antibody conformational ensembles withABodyBuilder4-STEROIDS

bioRxiv Apr 16, 2026
Conformational flexibility is fundamental to the function of many proteins and in the case of antibodies can impact key properties such as affinity and specificity. While it is possible to predict single, static protein structures with high accuracy,... read more 
bioinformatics

Reinforcement learning for closed-loop optimisation of spatiotemporal stimulation in patterned neuronal networks

bioRxiv Apr 16, 2026
Understanding how neuronal circuits transform inputs into outputs requires systematic perturbation under controlled conditions. In vitro neuronal networks can be cultured on microelectrode arrays (MEAs) that allow stimulation and recording, and micro... read more 
neuroscience

Multiscale transcriptomic organization of the human brain with DigitalBrain

bioRxiv Apr 16, 2026
The human brain varies across anatomical regions, cell types, development, ageing and disease states, yet existing single-cell transcriptomic resources remain fragmented and difficult to integrate into a unified biological model. Here we present Digi... read more 
bioinformatics

Learning to select computations in recurrent neural circuits

bioRxiv Apr 16, 2026
Two hallmarks of biological computation are its flexibility and efficiency. These features are often attributed to cognitive control processes that balance external utility against computational cost. However, how the brain could implement such adapt... read more 
neuroscience

LinkLlama: Enabling Large Language Model for Chemically Reasonable Linker Design

bioRxiv Apr 16, 2026
Fragment-based drug discovery (FBDD) relies heavily on the design of chemically viable linkers to connect fragments binding to different pocket regions into potent lead molecules. While recent generative models have advanced spatial fragment linking,... read more 
bioinformatics

A generative AI framework for disease-specific lung microtissue bioengineering

bioRxiv Apr 16, 2026
Generative Lung Architecture Modeling (GLAM) is an integrated bioengineering framework that couples high-resolution three-dimensional tissue imaging with generative artificial intelligence to de novo design and 3D-bioprint anatomically detailed lung ... read more 
bioengineering

Highly Accurate Estimation of the Fold Accuracy of Protein Structural Models

bioRxiv Apr 16, 2026
The function of a protein is intrinsically linked to its three-dimensional fold, and deep learning has revolutionized the field by enabling high-accuracy structure prediction at an unprecedented scale. Nevertheless, the growing deployment of these pr... read more 
bioinformatics

Latent neural network representations of the brain reflect broad-scale adolescent phenotypic variation

bioRxiv Apr 16, 2026
The adolescent brain is attuned to social and environmental exploration, allowing behavioral adaptation as experiences shape lasting patterns of morphological organization. Using a convolutional neural network on longitudinal structural MRI data, we ... read more 
neuroscience
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