Research graph
References from Artificial intelligence in medical image processing and translational science. Local targets link to admitted publications; unresolved targets remain external evidence.
Accurate structure prediction of biomolecular interactions with AlphaFold 3
10.1038/s41586-024-07487-w · 2024 · External reference
Multimodal biomedical AI
10.1038/s41591-022-01981-2 · 2022 · External reference
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
2014 · External reference
OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
2022 · External reference
Brain tumor classification using a combination of variational autoencoders and generative adversarial networks
10.3390/biomedicines10020223 · 2022 · External reference
Unresolved reference
2024 · External reference
Voxel-by-voxel correlation between radiologically radiation induced lung injury and dose after image-guided, intensity modulated radiotherapy for lung tumors
10.1016/j.ejmp.2017.09.127 · 2017 · External reference
The living heart project: a robust and integrative simulator for human heart function
10.1016/j.euromechsol.2014.04.001 · 2014 · External reference
Tissue microarray (TMA) technology: miniaturized pathology archives for high-throughputin situ studies
10.1002/path.893 · 2001 · External reference
Addressing artificial intelligence bias in retinal diagnostics
10.1167/tvst.10.2.13 · 2021 · External reference
Tribulations and future opportunities for artificial intelligence in precision medicine
10.1186/s12967-024-05067-0 · 2024 · External reference
A survey on deep learning applied to medical images: from simple artificial neural networks to generative models
10.1007/s00521-022-07953-4 · 2023 · External reference
Digital twins: the new frontier for personalized medicine?
10.3390/app13137940 · 2023 · External reference
CryptoSite: expanding the druggable proteome by characterization and prediction of cryptic binding sites
10.1016/j.jmb.2016.01.029 · 2016 · External reference
Radiation planning assistant—a web-based tool to support high-quality radiotherapy in clinics with limited resources
10.3791/65504 · 2023 · External reference
ChatGPT in medical imaging higher education
10.1016/j.radi.2023.05.011 · 2023 · External reference
Unveiling the influence of AI predictive analytics on patient outcomes: a comprehensive narrative review
2024 · External reference
Adaptive radiotherapy: next-generation radiotherapy
10.3390/cancers16061206 · 2024 · External reference
Toward generalizability in the deployment of artificial intelligence in radiology: role of computation stress testing to overcome underspecification
10.1148/ryai.2021210097 · 2021 · External reference
Protein complex prediction with AlphaFold-multimer
2021 · External reference
Helixfold-multimer: elevating protein complex structure prediction to new heights
2024 · External reference
Geometry-enhanced molecular representation learning for property prediction
10.1038/s42256-021-00438-4 · 2022 · External reference
Deep convolutional neural network for segmentation of thoracic organs‐at‐risk using cropped 3D images
10.1002/mp.13466 · 2019 · External reference
Deformable image registration with deep network priors: a study on longitudinal PET images
10.1088/1361-6560/ac7e17 · 2022 · External reference
ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support
10.1093/nar/gkae236 · 2024 · External reference
Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery
10.1021/acscentsci.0c00229 · 2020 · External reference
An “intelligent” workstation for computer-aided diagnosis
10.1148/radiographics.13.3.8316671 · 1993 · External reference
Explainable AI (XAI) in image segmentation in medicine, industry, and beyond: a survey
10.1016/j.icte.2024.09.008 · 2024 · External reference
Bayer’s in silico ADMET platform: a journey of machine learning over the past two decades
10.1016/j.drudis.2020.07.001 · 2020 · External reference
Accelerating high-throughput virtual screening through molecular pool-based active learning
10.1039/d0sc06805e · 2021 · External reference
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
10.1038/s41467-019-11994-0 · 2019 · External reference
AlloPred: prediction of allosteric pockets on proteins using normal mode perturbation analysis
10.1186/s12859-015-0771-1 · 2015 · External reference
OPTIMAM mammography image database: a large-scale resource of mammography images and clinical data
10.1148/ryai.2020200103 · 2021 · External reference
New technology add-on payment (NTAP) for Viz LVO: a win for stroke care
10.1136/neurintsurg-2020-016897 · 2021 · External reference
Artificial intelligence in radiology
10.1038/s41568-018-0016-5 · 2018 · External reference
Allosite: a method for predicting allosteric sites
10.1093/bioinformatics/btt399 · 2013 · External reference
Remote patient monitoring using artificial intelligence
2020 · External reference
Identification of potential aldose reductase inhibitors using convolutional neural network-based in silico screening
10.1021/acs.jcim.3c00547 · 2023 · External reference
Artificial neural network models driven novel virtual screening workflow for the identification and biological evaluation of BACE1 inhibitors
10.1002/minf.202200113 · 2023 · External reference
Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents
10.1007/s11030-021-10274-8 · 2021 · External reference
Digital twins for health: a scoping review
10.1038/s41746-024-01073-0 · 2024 · External reference
Denoising diffusion probabilistic models for 3D medical image generation
10.1038/s41598-023-34341-2 · 2023 · External reference
Diagnostic accuracy of IDX-DR for detecting diabetic retinopathy: a systematic review and meta-analysis
10.1016/j.ajo.2025.02.022 · 2025 · External reference
Unresolved reference
2023 · External reference
ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins
10.1016/j.pbiomolbio.2017.02.005 · 2017 · External reference
Natural language processing systems for capturing and standardizing unstructured clinical information: a systematic review
10.1016/j.jbi.2017.07.012 · 2017 · External reference
The future of AI and informatics in radiology: 10 predictions
10.1148/radiol.231114 · 2023 · External reference
Using digital twins for precision medicine in vascular surgery
10.1016/j.avsg.2020.04.042 · 2020 · External reference
A review of deep-learning-based approaches for attenuation correction in positron emission tomography
10.1109/trpms.2020.3009269 · 2021 · External reference
A curated mammography data set for use in computer-aided detection and diagnosis research
10.1038/sdata.2017.177 · 2017 · External reference
EQUIBIND: a geometric deep learning-based protein-ligand binding prediction method
10.5582/ddt.2023.01063 · 2023 · External reference
Multistate and functional protein design using RoseTTAFold sequence space diffusion
2024 · External reference
Artificial intelligence–based breast cancer nodal metastasis detection insights into the black box for pathologists
10.5858/arpa.2018-0147-oa · 2019 · External reference
A Bayesian machine learning approach for drug target identification using diverse data types
10.1038/s41467-019-12928-6 · 2019 · External reference
Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing
10.1093/bjrai/ubae003 · 2024 · External reference
RoseTTAFold expands to all-atom for biomolecular prediction and design
2024 · External reference
Feeding the data monster: data science in head and neck cancer for personalized therapy
10.1016/j.jacr.2019.05.045 · 2019 · External reference
GNINA 1.3: the next increment in molecular docking with deep learning
10.1186/s13321-025-00973-x · 2025 · External reference
RadImageNet: an open radiologic deep learning research dataset for effective transfer learning
10.1148/ryai.210315 · 2022 · External reference
Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network
10.1038/s41467-023-36699-3 · 2023 · External reference
ColabFold: making protein folding accessible to all
10.1038/s41592-022-01488-1 · 2022 · External reference
Neuroimaging in the era of artificial intelligence: current applications
2022 · External reference
INbreast: toward a full-field digital mammographic database
10.1016/j.acra.2011.09.014 · 2012 · External reference
Segmentation of anatomical structures of the left heart from echocardiographic images using deep learning
10.3390/diagnostics13101683 · 2023 · External reference
A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images
10.1002/mp.13519 · 2019 · External reference
Explainable AI in radiology: a white paper of the Italian Society of Medical and Interventional Radiology
10.1007/s11547-023-01634-5 · 2023 · External reference
Deep feature transfer learning in combination with traditional features predicts survival among patients with lung adenocarcinoma
10.18383/j.tom.2016.00211 · 2016 · External reference
DeepSeeNet: a deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs
10.1016/j.ophtha.2018.11.015 · 2019 · External reference
Imaging diagnosis and follow-up of advanced prostate cancer: clinical perspectives and state of the art
10.1148/radiol.2019181931 · 2019 · External reference
Learning from the experts: from expert systems to machine-learned diagnosis models
2018 · External reference
Deep learning for medical image segmentation: state-of-the-art advancements and challenges
10.1016/j.imu.2024.101504 · 2024 · External reference
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
10.1038/s42256-021-00307-0 · 2021 · External reference
The role of medical image modalities and AI in the early detection, diagnosis and grading of retinal diseases: a survey
10.3390/bioengineering9080366 · 2022 · External reference
Deep learning for automated, motion-resolved tumor segmentation in radiotherapy
10.1038/s41698-025-00970-1 · 2025 · External reference
A review of deep learning and generative adversarial networks applications in medical image analysis
10.1007/s00530-024-01349-1 · 2024 · External reference
Learning rigid image registration utilizing convolutional neural networks for medical image registration
2018 · External reference
Basic artificial intelligence techniques
10.1016/j.rcl.2021.06.003 · 2021 · External reference
The mammographic images analysis society digital mammogram database
1994 · External reference
Medical image registration via neural fields
10.1016/j.media.2024.103249 · 2024 · External reference
ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries
10.1093/bioinformatics/btae416 · 2024 · External reference
Artificial intelligence and surgery
10.1002/ags3.12766 · 2024 · External reference
Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment
10.1186/s12911-024-02444-z · 2024 · External reference
AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations
10.1093/nar/gkaa338 · 2020 · External reference
Synthetic CT image generation of shape-controlled lung cancer using semi-conditional InfoGAN and its applicability for type classification
10.1007/s11548-021-02308-1 · 2021 · External reference
Evaluation of auto-segmentation accuracy of cloud-based artificial intelligence and atlas-based models
10.1186/s13014-021-01896-1 · 2021 · External reference
Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery
10.1186/s13014-023-02246-z · 2023 · External reference
Autoregressive sequence modeling for 3D medical image representation
10.1609/aaai.v39i8.32848 · 2025 · External reference
Generative adversarial networks: a primer for radiologists
10.1148/rg.2021200151 · 2021 · External reference
Scalable high-performance image registration framework by unsupervised deep feature representations learning
10.1109/tbme.2015.2496253 · 2016 · External reference
Vision transformers: the next frontier for deep learning-based ophthalmic image analysis
10.4103/sjopt.sjopt_91_23 · 2023 · External reference
High-resolution de novo structure prediction from primary sequence
2022 · External reference
Artificial intelligence: a powerful paradigm for scientific research
10.1016/j.xinn.2021.100179 · 2021 · External reference
Regulatory aspects of the use of artificial intelligence medical software
10.1016/j.semradonc.2022.06.012 · 2022 · External reference
Diagnostic accuracy of artificial intelligence in virtual primary care
10.1016/j.mcpdig.2023.08.002 · 2023 · External reference
Target identification among known drugs by deep learning from heterogeneous networks
10.1039/c9sc04336e · 2020 · External reference
AlloReverse: multiscale understanding among hierarchical allosteric regulations
10.1093/nar/gkad279 · 2023 · External reference
Applications of a deep learning method for anti-aliasing and super-resolution in MRI
10.1016/j.mri.2019.05.038 · 2019 · External reference
Medical SAM 2: segment medical images as video via segment anything model 2
2024 · External reference
Artificial intelligence and surgery
10.1002/ags3.12766 · ExternalCitation · doi-reference
Artificial neural network models driven novel virtual screening workflow for the identification and biological evaluation of BACE1 inhibitors
10.1002/minf.202200113 · ExternalCitation · doi-reference
Deep convolutional neural network for segmentation of thoracic organs‐at‐risk using cropped 3D images
10.1002/mp.13466 · ExternalCitation · doi-reference
A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images
10.1002/mp.13519 · ExternalCitation · doi-reference
Tissue microarray (TMA) technology: miniaturized pathology archives for high-throughputin situ studies
10.1002/path.893 · ExternalCitation · doi-reference
A survey on deep learning applied to medical images: from simple artificial neural networks to generative models
10.1007/s00521-022-07953-4 · ExternalCitation · doi-reference
A review of deep learning and generative adversarial networks applications in medical image analysis
10.1007/s00530-024-01349-1 · ExternalCitation · doi-reference
Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents
10.1007/s11030-021-10274-8 · ExternalCitation · doi-reference
Explainable AI in radiology: a white paper of the Italian Society of Medical and Interventional Radiology
10.1007/s11547-023-01634-5 · ExternalCitation · doi-reference
Synthetic CT image generation of shape-controlled lung cancer using semi-conditional InfoGAN and its applicability for type classification
10.1007/s11548-021-02308-1 · ExternalCitation · doi-reference
INbreast: toward a full-field digital mammographic database
10.1016/j.acra.2011.09.014 · ExternalCitation · doi-reference
Diagnostic accuracy of IDX-DR for detecting diabetic retinopathy: a systematic review and meta-analysis
10.1016/j.ajo.2025.02.022 · ExternalCitation · doi-reference
Using digital twins for precision medicine in vascular surgery
10.1016/j.avsg.2020.04.042 · ExternalCitation · doi-reference
Bayer’s in silico ADMET platform: a journey of machine learning over the past two decades
10.1016/j.drudis.2020.07.001 · ExternalCitation · doi-reference
Voxel-by-voxel correlation between radiologically radiation induced lung injury and dose after image-guided, intensity modulated radiotherapy for lung tumors
10.1016/j.ejmp.2017.09.127 · ExternalCitation · doi-reference
The living heart project: a robust and integrative simulator for human heart function
10.1016/j.euromechsol.2014.04.001 · ExternalCitation · doi-reference
Explainable AI (XAI) in image segmentation in medicine, industry, and beyond: a survey
10.1016/j.icte.2024.09.008 · ExternalCitation · doi-reference
Deep learning for medical image segmentation: state-of-the-art advancements and challenges
10.1016/j.imu.2024.101504 · ExternalCitation · doi-reference
Feeding the data monster: data science in head and neck cancer for personalized therapy
10.1016/j.jacr.2019.05.045 · ExternalCitation · doi-reference
Natural language processing systems for capturing and standardizing unstructured clinical information: a systematic review
10.1016/j.jbi.2017.07.012 · ExternalCitation · doi-reference
CryptoSite: expanding the druggable proteome by characterization and prediction of cryptic binding sites
10.1016/j.jmb.2016.01.029 · ExternalCitation · doi-reference
Diagnostic accuracy of artificial intelligence in virtual primary care
10.1016/j.mcpdig.2023.08.002 · ExternalCitation · doi-reference
Medical image registration via neural fields
10.1016/j.media.2024.103249 · ExternalCitation · doi-reference
Applications of a deep learning method for anti-aliasing and super-resolution in MRI
10.1016/j.mri.2019.05.038 · ExternalCitation · doi-reference
DeepSeeNet: a deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs
10.1016/j.ophtha.2018.11.015 · ExternalCitation · doi-reference
ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins
10.1016/j.pbiomolbio.2017.02.005 · ExternalCitation · doi-reference
ChatGPT in medical imaging higher education
10.1016/j.radi.2023.05.011 · ExternalCitation · doi-reference
Basic artificial intelligence techniques
10.1016/j.rcl.2021.06.003 · ExternalCitation · doi-reference
Regulatory aspects of the use of artificial intelligence medical software
10.1016/j.semradonc.2022.06.012 · ExternalCitation · doi-reference
Artificial intelligence: a powerful paradigm for scientific research
10.1016/j.xinn.2021.100179 · ExternalCitation · doi-reference
Identification of potential aldose reductase inhibitors using convolutional neural network-based in silico screening
10.1021/acs.jcim.3c00547 · ExternalCitation · doi-reference
Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery
10.1021/acscentsci.0c00229 · ExternalCitation · doi-reference
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
10.1038/s41467-019-11994-0 · ExternalCitation · doi-reference
A Bayesian machine learning approach for drug target identification using diverse data types
10.1038/s41467-019-12928-6 · ExternalCitation · doi-reference
Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network
10.1038/s41467-023-36699-3 · ExternalCitation · doi-reference
Artificial intelligence in radiology
10.1038/s41568-018-0016-5 · ExternalCitation · doi-reference
Accurate structure prediction of biomolecular interactions with AlphaFold 3
10.1038/s41586-024-07487-w · ExternalCitation · doi-reference
Multimodal biomedical AI
10.1038/s41591-022-01981-2 · ExternalCitation · doi-reference
ColabFold: making protein folding accessible to all
10.1038/s41592-022-01488-1 · ExternalCitation · doi-reference
Denoising diffusion probabilistic models for 3D medical image generation
10.1038/s41598-023-34341-2 · ExternalCitation · doi-reference
Deep learning for automated, motion-resolved tumor segmentation in radiotherapy
10.1038/s41698-025-00970-1 · ExternalCitation · doi-reference
Digital twins for health: a scoping review
10.1038/s41746-024-01073-0 · ExternalCitation · doi-reference
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
10.1038/s42256-021-00307-0 · ExternalCitation · doi-reference
Geometry-enhanced molecular representation learning for property prediction
10.1038/s42256-021-00438-4 · ExternalCitation · doi-reference
A curated mammography data set for use in computer-aided detection and diagnosis research
10.1038/sdata.2017.177 · ExternalCitation · doi-reference
Target identification among known drugs by deep learning from heterogeneous networks
10.1039/c9sc04336e · ExternalCitation · doi-reference
Accelerating high-throughput virtual screening through molecular pool-based active learning
10.1039/d0sc06805e · ExternalCitation · doi-reference
Deformable image registration with deep network priors: a study on longitudinal PET images
10.1088/1361-6560/ac7e17 · ExternalCitation · doi-reference
ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries
10.1093/bioinformatics/btae416 · ExternalCitation · doi-reference
Allosite: a method for predicting allosteric sites
10.1093/bioinformatics/btt399 · ExternalCitation · doi-reference
Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing
10.1093/bjrai/ubae003 · ExternalCitation · doi-reference
AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations
10.1093/nar/gkaa338 · ExternalCitation · doi-reference
AlloReverse: multiscale understanding among hierarchical allosteric regulations
10.1093/nar/gkad279 · ExternalCitation · doi-reference
ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support
10.1093/nar/gkae236 · ExternalCitation · doi-reference
Scalable high-performance image registration framework by unsupervised deep feature representations learning
10.1109/tbme.2015.2496253 · ExternalCitation · doi-reference
A review of deep-learning-based approaches for attenuation correction in positron emission tomography
10.1109/trpms.2020.3009269 · ExternalCitation · doi-reference
New technology add-on payment (NTAP) for Viz LVO: a win for stroke care
10.1136/neurintsurg-2020-016897 · ExternalCitation · doi-reference
An “intelligent” workstation for computer-aided diagnosis
10.1148/radiographics.13.3.8316671 · ExternalCitation · doi-reference
Imaging diagnosis and follow-up of advanced prostate cancer: clinical perspectives and state of the art
10.1148/radiol.2019181931 · ExternalCitation · doi-reference
The future of AI and informatics in radiology: 10 predictions
10.1148/radiol.231114 · ExternalCitation · doi-reference
Generative adversarial networks: a primer for radiologists
10.1148/rg.2021200151 · ExternalCitation · doi-reference
OPTIMAM mammography image database: a large-scale resource of mammography images and clinical data
10.1148/ryai.2020200103 · ExternalCitation · doi-reference
Toward generalizability in the deployment of artificial intelligence in radiology: role of computation stress testing to overcome underspecification
10.1148/ryai.2021210097 · ExternalCitation · doi-reference
RadImageNet: an open radiologic deep learning research dataset for effective transfer learning
10.1148/ryai.210315 · ExternalCitation · doi-reference
Addressing artificial intelligence bias in retinal diagnostics
10.1167/tvst.10.2.13 · ExternalCitation · doi-reference
AlloPred: prediction of allosteric pockets on proteins using normal mode perturbation analysis
10.1186/s12859-015-0771-1 · ExternalCitation · doi-reference
Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment
10.1186/s12911-024-02444-z · ExternalCitation · doi-reference
Tribulations and future opportunities for artificial intelligence in precision medicine
10.1186/s12967-024-05067-0 · ExternalCitation · doi-reference
Evaluation of auto-segmentation accuracy of cloud-based artificial intelligence and atlas-based models
10.1186/s13014-021-01896-1 · ExternalCitation · doi-reference
Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery
10.1186/s13014-023-02246-z · ExternalCitation · doi-reference
GNINA 1.3: the next increment in molecular docking with deep learning
10.1186/s13321-025-00973-x · ExternalCitation · doi-reference
Autoregressive sequence modeling for 3D medical image representation
10.1609/aaai.v39i8.32848 · ExternalCitation · doi-reference
Deep feature transfer learning in combination with traditional features predicts survival among patients with lung adenocarcinoma
10.18383/j.tom.2016.00211 · ExternalCitation · doi-reference
Digital twins: the new frontier for personalized medicine?
10.3390/app13137940 · ExternalCitation · doi-reference
The role of medical image modalities and AI in the early detection, diagnosis and grading of retinal diseases: a survey
10.3390/bioengineering9080366 · ExternalCitation · doi-reference
Brain tumor classification using a combination of variational autoencoders and generative adversarial networks
10.3390/biomedicines10020223 · ExternalCitation · doi-reference
Adaptive radiotherapy: next-generation radiotherapy
10.3390/cancers16061206 · ExternalCitation · doi-reference
Segmentation of anatomical structures of the left heart from echocardiographic images using deep learning
10.3390/diagnostics13101683 · ExternalCitation · doi-reference
Radiation planning assistant—a web-based tool to support high-quality radiotherapy in clinics with limited resources
10.3791/65504 · ExternalCitation · doi-reference
Vision transformers: the next frontier for deep learning-based ophthalmic image analysis
10.4103/sjopt.sjopt_91_23 · ExternalCitation · doi-reference
EQUIBIND: a geometric deep learning-based protein-ligand binding prediction method
10.5582/ddt.2023.01063 · ExternalCitation · doi-reference
Artificial intelligence–based breast cancer nodal metastasis detection insights into the black box for pathologists
10.5858/arpa.2018-0147-oa · ExternalCitation · doi-reference
