Journal & Article

Interdisciplinary Applications

I/F
# Journal I/F

Nature Machine Intelligence

AI and the long game Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals Synthetic X‑ray‑driven tracking and control of miniature medical devices Benchmarking large language models on safety risks in scientific laboratories Jointly modeling cardiovascular biomarkers Addendum: Resolving data bias improves generalization in binding affinity prediction Multi-agent AI systems need transparency Modelling drug-induced cellular perturbation responses with a biologically informed dual-branch transformer Proposing and solving olympiad geometry with guided tree search Teaching machines to blend electrolyte cocktails A unified predictive and generative solution for liquid electrolyte formulation On the troubling rise of generative AI suspicion in academic publishing Identifying spatial single-cell-level interactions with graph transformer Authorization of prognostic AI medical devices Attributing and situating knowledge cannot be left to language models Visual language models show widespread visual deficits on neuropsychological tests A flaw in using pretrained protein language models in protein–protein interaction inference models Reusability Report: Evaluating the performance of a meta-learning foundation model on predicting the antibacterial activity of natural products When large language models are reliable for judging empathic communication What matters in building vision–language–action models for generalist robots A federated graph learning method to realize multi-party collaboration for molecular discovery Parallel hierarchical encoding of linguistic representations in the human auditory cortex and recurrent automatic speech recognition systems Preconditioned inexact stochastic ADMM for deep models Meta-designing quantum experiments with language models Author Correction: Mask-prior-guided denoising diffusion improves inverse protein folding A large-scale randomized study of large language model feedback in peer review Deep generative classification of blood cell morphology. Reusability report: A distributed strategy for solving combinatorial optimization problems with hypergraph neural networks. Are neural network representations universal or idiosyncratic? Accelerating molecular dynamics by going with the flow. Learning conformational flexibility of immune receptors. Overcoming classic challenges for artificial neural networks by providing incentives and practice. Towards deployment-centric multimodal AI beyond vision and language. Flow matching for accelerated simulation of atomic transport in crystalline materials. Cooperative multi-view integration with a scalable and interpretable model explainer. Tailored structured peptide design with a key-cutting machine approach. Resolving data bias improves generalization in binding affinity prediction. A neural symbolic model for space physics. Single-unit activations confer inductive biases for emergent circuit solutions to cognitive tasks. Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions. Efficient protein structure generation with sparse denoising models Towards responsible geospatial foundation models. The importance of negative training data for robust antibody binding prediction. Training data composition determines machine learning generalization and biological rule discovery. Electron-density-informed effective and reliable de novo molecular design and optimization with ED2Mol. Emotional risks of AI companions demand attention Data meets prior knowledge for interpretable mechanistic inference in biology: Recovering biological networks Combining grasping and rotation with a spherical robot hand mechanism Designing metamaterials with programmable nonlinear responses and geometric constraints in graph space Integrating multimodal cancer data using deep latent variable path modelling