Nature Machine Intelligence

Article	Citations
An interpretable mortality prediction model for COVID-19 patients	665
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators	620
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans	602
Shortcut learning in deep neural networks	577
Secure, privacy-preserving and federated machine learning in medical imaging	497
Drug discovery with explainable artificial intelligence	432
Deep learning for tomographic image reconstruction	246
Machine learning pipeline for battery state-of-health estimation	245
AI for radiographic COVID-19 detection selects shortcuts over signal	239
An open source machine learning framework for efficient and transparent systematic reviews	236
Molecular contrastive learning of representations via graph neural networks	199
Inverse design of nanoporous crystalline reticular materials with deep generative models	177
Finding key players in complex networks through deep reinforcement learning	176
Expanding functional protein sequence spaces using generative adversarial networks	172
Geometry-enhanced molecular representation learning for property prediction	165
End-to-end privacy preserving deep learning on multi-institutional medical imaging	164
The carbon impact of artificial intelligence	163
Ensemble deep learning in bioinformatics	163
Causal inference and counterfactual prediction in machine learning for actionable healthcare	155
Improved protein structure prediction by deep learning irrespective of co-evolution information	142
Concept whitening for interpretable image recognition	126
Development of metaverse for intelligent healthcare	126
Mapping the space of chemical reactions using attention-based neural networks	124
Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks	122
Enabling the future of colonoscopy with intelligent and autonomous magnetic manipulation	119

Deep learning-based prediction of the T cell receptor–antigen binding specificity	112
The rise of robots in surgical environments during COVID-19	109
Advances, challenges and opportunities in creating data for trustworthy AI	108
Geometric deep learning on molecular representations	108
Database-independent molecular formula annotation using Gibbs sampling through ZODIAC	104
Generating three-dimensional structures from a two-dimensional slice with generative adversarial network-based dimensionality expansion	104
Bioinspired acousto-magnetic microswarm robots with upstream motility	102
A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing	102
Neural circuit policies enabling auditable autonomy	101
Towards neural Earth system modelling by integrating artificial intelligence in Earth system science	101
Code-free deep learning for multi-modality medical image classification	100
Estimation of continuous valence and arousal levels from faces in naturalistic conditions	97
Dual use of artificial-intelligence-powered drug discovery	97
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data	96
Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network	96
Machine learning and computation-enabled intelligent sensor design	95
High-accuracy prostate cancer pathology using deep learning	95
Towards a new generation of artificial intelligence in China	95
Prediction of water stability of metal–organic frameworks using machine learning	94
Making deep neural networks right for the right scientific reasons by interacting with their explanations	93
A soft robot that adapts to environments through shape change	93
Origami-inspired miniature manipulator for teleoperated microsurgery	92
Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms	91
Machine learning and algorithmic fairness in public and population health	89
Deep learning incorporating biologically inspired neural dynamics and in-memory computing	89
Automating turbulence modelling by multi-agent reinforcement learning	89
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors	88
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning	88
The transformational role of GPU computing and deep learning in drug discovery	83
Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis	83
Artificial intelligence cooperation to support the global response to COVID-19	81
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks	81
Three types of incremental learning	81
Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning	80
Learning functional properties of proteins with language models	78
Controllable protein design with language models	78
A definition, benchmark and database of AI for social good initiatives	76
Using online verification to prevent autonomous vehicles from causing accidents	75
Stable learning establishes some common ground between causal inference and machine learning	75
Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations	73
A soft thumb-sized vision-based sensor with accurate all-round force perception	73
Improving performance of deep learning models with axiomatic attribution priors and expected gradients	73
A versatile deep learning architecture for classification and label-free prediction of hyperspectral images	72
Morphological and molecular breast cancer profiling through explainable machine learning	72
A geometric deep learning approach to predict binding conformations of bioactive molecules	71
An embedded ethics approach for AI development	71
Biological underpinnings for lifelong learning machines	69
AI-generated characters for supporting personalized learning and well-being	68
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning	67
Predictive control of aerial swarms in cluttered environments	67

Large pre-trained language models contain human-like biases of what is right and wrong to do	64
Governing AI safety through independent audits	63
Teaching recurrent neural networks to infer global temporal structure from local examples	62
Encoding of tactile information in hand via skin-integrated wireless haptic interface	61
A transformer-based model to predict peptide–HLA class I binding and optimize mutated peptides for vaccine design	60
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin	59
A case-based interpretable deep learning model for classification of mass lesions in digital mammography	59
Deep neural networks identify sequence context features predictive of transcription factor binding	58
Extraction of protein dynamics information from cryo-EM maps using deep learning	57
Human–AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support	57
Combinatorial optimization with physics-inspired graph neural networks	57
Large-scale chemical language representations capture molecular structure and properties	57
Fast and energy-efficient neuromorphic deep learning with first-spike times	56
Optimized spiking neurons can classify images with high accuracy through temporal coding with two spikes	56
Simultaneous deep generative modelling and clustering of single-cell genomic data	56
Molecular convolutional neural networks with DNA regulatory circuits	55
Parameter-efficient fine-tuning of large-scale pre-trained language models	55
Predicting tumour mutational burden from histopathological images using multiscale deep learning	55
Learning function from structure in neuromorphic networks	54
When causal inference meets deep learning	54
A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets	54
Interpretable deep-learning models to help achieve the Sustainable Development Goals	53
Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions	52
Benchmarking saliency methods for chest X-ray interpretation	52
Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework	52
Chemical language models enable navigation in sparsely populated chemical space	50
Chemically programmable microrobots weaving a web from hormones	49
Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy	49
Actor neural networks for the robust control of partially measured nonlinear systems showcased for image propagation through diffuse media	48
Improving representations of genomic sequence motifs in convolutional networks with exponential activations	47
Machine Learning for COVID-19 needs global collaboration and data-sharing	47
Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding	46
Improving the quality of machine learning in health applications and clinical research	46
Radiological tumour classification across imaging modality and histology	45
Large language models associate Muslims with violence	45
Multiscale simulations of complex systems by learning their effective dynamics	45
A biological perspective on evolutionary computation	43
Deep recurrent optical flow learning for particle image velocimetry data	43
External validation demonstrates limited clinical utility of the interpretable mortality prediction model for patients with COVID-19	43
A machine learning platform to estimate anti-SARS-CoV-2 activities	43
The challenges of deploying artificial intelligence models in a rapidly evolving pandemic	43
Experimental discovery of structure–property relationships in ferroelectric materials via active learning	41
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware	41
Skills for physical artificial intelligence	41
Real-world embodied AI through a morphologically adaptive quadruped robot	40
Automatic strain sensor design via active learning and data augmentation for soft machines	39
Improving healthcare operations management with machine learning	39
A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data	39
Increasing generality in machine learning through procedural content generation	39
Protein function prediction is improved by creating synthetic feature samples with generative adversarial networks	39
An interpretable deep-learning architecture of capsule networks for identifying cell-type gene expression programs from single-cell RNA-sequencing data	39
Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification	38
A novel machine learning framework for automated biomedical relation extraction from large-scale literature repositories	38
Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities	38
The neural resource allocation problem when enhancing human bodies with extra robotic limbs	38
Institutionalizing ethics in AI through broader impact requirements	38
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires	37
Predicting myocardial infarction through retinal scans and minimal personal information	37
Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices	37
Enhancing optical-flow-based control by learning visual appearance cues for flying robots	37
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling	36
Deep learning-based robust positioning for all-weather autonomous driving	36
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments	35
Intelligent problem-solving as integrated hierarchical reinforcement learning	35
Bringing artificial intelligence to business management	35
Algorithms to estimate Shapley value feature attributions	35
Tracking the debate on COVID-19 surveillance tools	35
Interpretable bilinear attention network with domain adaptation improves drug–target prediction	34
Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy	34
Multimodal data fusion for cancer biomarker discovery with deep learning	34
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks	34
Generalized radiograph representation learning via cross-supervision between images and free-text radiology reports	34
Automating crystal-structure phase mapping by combining deep learning with constraint reasoning	33
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	33
Pan-Peptide Meta Learning for T-cell receptor–antigen binding recognition	32
Minimal-uncertainty prediction of general drug-likeness based on Bayesian neural networks	32
A deep generative model enables automated structure elucidation of novel psychoactive substances	32
Neurons learn by predicting future activity	32
Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries	32
Accelerated rational PROTAC design via deep learning and molecular simulations	32

Deep learning prediction of patient response time course from early data via neural-pharmacokinetic/pharmacodynamic modelling	31
Accelerating evidence-informed decision-making for the Sustainable Development Goals using machine learning	31
Autoregressive neural-network wavefunctions for ab initio quantum chemistry	31
Quantifying the spatial homogeneity of urban road networks via graph neural networks	31
Deep learning STEM-EDX tomography of nanocrystals	31
Cross-validation is safe to use	30
Visual speech recognition for multiple languages in the wild	30
Mixed-modality speech recognition and interaction using a wearable artificial throat	30
Direct-to-consumer medical machine learning and artificial intelligence applications	30
Large language models challenge the future of higher education	30
An automated framework for efficiently designing deep convolutional neural networks in genomics	30
Artificial intelligence in a crisis needs ethics with urgency	30
Segmentation of neurons from fluorescence calcium recordings beyond real time	29
Understanding adversarial examples requires a theory of artefacts for deep learning	29
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning	29
Variational neural annealing	29
The AI writing on the wall	28
A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputation	28
Designing clinically translatable artificial intelligence systems for high-dimensional medical imaging	28
Global voxel transformer networks for augmented microscopy	28
Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields	28
Regulating AI in medicine in the United States and Europe	27
A deep generative model for molecule optimization via one fragment modification	27
AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy	27
Interpretable socioeconomic status inference from aerial imagery through urban patterns	26
Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning	26
Transformer-based protein generation with regularized latent space optimization	26
Artificial microtubules for rapid and collective transport of magnetic microcargoes	25
Machine learning to guide the use of adjuvant therapies for breast cancer	25
Disentangling automatic and semi-automatic approaches to the optimization-based design of control software for robot swarms	25
Regression Transformer enables concurrent sequence regression and generation for molecular language modelling	25
Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider	25
Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks	25
Physics-based machine learning for subcellular segmentation in living cells	24
Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines	24
Unassisted noise reduction of chemical reaction datasets	24
Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations	23
A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applications	23
Harnessing the power of artificial intelligence to transform hearing healthcare and research	23
Echo state graph neural networks with analogue random resistive memory arrays	23
Data-driven discovery of intrinsic dynamics	23
Geometric deep learning reveals the spatiotemporal features of microscopic motion	22
Why it is time to stop ostracizing social robots	22
Replication of a mortality prediction model in Dutch patients with COVID-19	22
Closed-form continuous-time neural networks	21
Learning MRI artefact removal with unpaired data	21
Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network	21
Iterative human and automated identification of wildlife images	21
Integration of millions of transcriptomes using batch-aware triplet neural networks	20
Multimodal learning with graphs	20
Generative AI entails a credit–blame asymmetry	20
Optimizing molecules using efficient queries from property evaluations	20
Search and rescue with airborne optical sectioning	20
Decoding speech perception from non-invasive brain recordings	20
Inferring transcription factor regulatory networks from single-cell ATAC-seq data based on graph neural networks	20
Design of potent antimalarials with generative chemistry	20
Exploring the cloud of variable importance for the set of all good models	19
Knowledge graph-enhanced molecular contrastive learning with functional prompt	19
Evaluating deep learning for predicting epigenomic profiles	19
Moving beyond generalization to accurate interpretation of flexible models	19
Federated disentangled representation learning for unsupervised brain anomaly detection	19
A checklist for safe robot swarms	19
High-resolution radar road segmentation using weakly supervised learning	19
Neural Error Mitigation of Near-Term Quantum Simulations	19
Simple nearest-neighbour analysis meets the accuracy of compound potency predictions using complex machine learning models	19
Physical human–robot interaction for clinical care in infectious environments	19
Improving de novo molecular design with curriculum learning	19
Stretchable e-skin and transformer enable high-resolution morphological reconstruction for soft robots	18
Deep transfer operator learning for partial differential equations under conditional shift	18
An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors	18
Finding the ground state of spin Hamiltonians with reinforcement learning	18
Deep learning decodes the principles of differential gene expression	18
An ethical trajectory planning algorithm for autonomous vehicles	18
Labelling instructions matter in biomedical image analysis	18
Super-resolution generative adversarial networks of randomly-seeded fields	18
A context-aware deconfounding autoencoder for robust prediction of personalized clinical drug response from cell-line compound screening	17
Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions	17
Lessons from infant learning for unsupervised machine learning	17
Predicting functional effect of missense variants using graph attention neural networks	17
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations	17
Linguistically inspired roadmap for building biologically reliable protein language models	16
Limited applicability of a COVID-19 specific mortality prediction rule to the intensive care setting	16
An adaptive graph learning method for automated molecular interactions and properties predictions	16
A critical problem in benchmarking and analysis of evolutionary computation methods	16
From attribution maps to human-understandable explanations through Concept Relevance Propagation	16
Embodied intelligence weaves a better future	16
On the importance of ethnographic methods in AI research	15
Contrastive learning enables rapid mapping to multimodal single-cell atlas of multimillion scale	15
Protein function prediction for newly sequenced organisms	15
Simultaneous dimensionality reduction and integration for single-cell ATAC-seq data using deep learning	15
Transferring policy of deep reinforcement learning from simulation to reality for robotics	15
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model	15
A generalized-template-based graph neural network for accurate organic reactivity prediction	15
Interpreting neural networks for biological sequences by learning stochastic masks	14
Augmenting vascular disease diagnosis by vasculature-aware unsupervised learning	14