Democratizing AI

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation

Sheller, M. J., Reina, G. A., Edwards, B., Martin, J., & Bakas, S. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-11723-8_9 · Cited by 609 · see citing works

Design Characteristics of Studies Reporting the Performance of Artificial Intelligence Algorithms for Diagnostic Analysis of Medical Images: Results from Recently Published Papers

Kim, D. W., Jang, H. Y., Kim, K. W., Shin, Y., & Park, S. H. (2019) · Korean Journal of Radiology · doi:10.3348/kjr.2019.0025 · Cited by 459 · see citing works

A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop

Langlotz, C. P., Allen, B., Erickson, B. J., Kalpathy-Cramer, J., Bigelow, K., Cook, T. S., Flanders, A. E., Lungren, M. P., Mendelson, D. S., Rudie, J. D., et al. (2019) · Radiology · doi:10.1148/radiol.2019190613 · Cited by 368 · see citing works

Distributed deep learning networks among institutions for medical imaging

Chang, K., Balachandar, N., Lam, C., Yi, D., Brown, J., Beers, A., Rosen, B., Rubin, D. L., & Kalpathy-Cramer, J. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy017 · Cited by 340 · see citing works

Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning

Nishio, M., Sugiyama, O., Yakami, M., Ueno, S., Kubo, T., Kuroda, T., & Togashi, K. (2018) · PLoS ONE · doi:10.1371/journal.pone.0200721 · Cited by 170 · see citing works

A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop

Allen, B., Seltzer, S. E., Langlotz, C. P., Dreyer, K., Summers, R. M., Petrick, N., Marinac‐Dabic, D., Cruz, M. L., Alkasab, T. K., Hanisch, R. J., et al. (2019) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2019.04.014 · Cited by 128 · see citing works

The sustainability of artificial intelligence: an urbanistic viewpoint from the lens of smart and sustainable cities

Yigitcanlar, T., & Cugurullo, F. (2020) · Sustainability · doi:10.3390/su12208548 · Cited by 337 · see citing works

Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future ProspectsPreprint

Hadi, M. U., Al-Tashi, Q., Qureshi, R., Shah, A., Muneer, A., Irfan, M., Zafar, A., Shaikh, M. B., Akhtar, N., Hassan, S. Z., et al. (2023) · doi:10.36227/techrxiv.23589741.v4 · Cited by 173 · see citing works

2020 ACR Data Science Institute Artificial Intelligence Survey

Allen, B., Agarwal, S., Coombs, L. P., Wald, C., & Dreyer, K. J. (2021) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2021.04.002 · Cited by 154 · see citing works

Noninterpretive Uses of Artificial Intelligence in Radiology

Richardson, M. L., Garwood, E. R., Lee, Y. Z., Li, M., Lo, H. S., Nagaraju, A., Nguyen, X. V., Probyn, L. J., Rajiah, P. S., Sin, J. M., et al. (2020) · Academic Radiology · doi:10.1016/j.acra.2020.01.012 · Cited by 105 · see citing works

NoPeek: Information leakage reduction to share activations in distributed deep learning

Vepakomma, P., Singh, A., Gupta, O., & Raskar, R. (2020) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw51313.2020.00134 · Cited by 83 · see citing works

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups

Thompson, H. M., Sharma, B., Bhalla, S., Boley, R., McCluskey, C., Dligach, D., Churpek, M. M., Karnik, N. S., & Afshar, M. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab148 · Cited by 78 · see citing works

Using Generative Artificial Intelligence Tools in Cosmetic Surgery: A Study on Rhinoplasty, Facelifts, and Blepharoplasty Procedures

Lim, B., Seth, I., Kah, S., Sofiadellis, F., Ross, R. J., Rozen, W. M., & Cuomo, R. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12206524 · Cited by 53 · see citing works

AI and Data Democratisation for Intelligent Energy Management

Marinakis, V., Koutsellis, T., Νίκας, Α., & Doukas, H. (2021) · Energies · doi:10.3390/en14144341 · Cited by 53 · see citing works

Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future ProspectsPreprint

Hadi, M. U., Al-Tashi, Q., Qureshi, R., Shah, A., Muneer, A., Irfan, M., Zafar, A., Shaikh, M. B., Akhtar, N., Hassan, S. Z., et al. (2023) · doi:10.36227/techrxiv.23589741.v3 · Cited by 62 · see citing works

In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare

Topaloglu, M. Y., Morrell, E. M., Rajendran, S., & Topaloĝlu, Ü. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.746497 · Cited by 50 · see citing works

DeePaN: deep patient graph convolutional network integrating clinico-genomic evidence to stratify lung cancers for immunotherapy

Fang, C., Xu, D. H., Su, J., Dry, J. R., & Linghu, B. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00381-z · Cited by 50 · see citing works

“Democratizing” artificial intelligence in medicine and healthcare: Mapping the uses of an elusive term

Rubeis, G., Dubbala, K., & Metzler, I. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.902542 · Cited by 48 · see citing works

Preparing Middle Schoolers for a Machine Learning-Enabled Future Through Design-Oriented Pedagogy

Sanusi, I. T., Omidiora, J. O., Oyelere, S. S., Vartiainen, H., Suhonen, J. T., & Tukiainen, M. (2023) · IEEE Access · doi:10.1109/access.2023.3269025 · Cited by 28 · see citing works

From Concept to Implementation: The Data-Centric Development Process for AI in Industry

Luley, P.-P., Deriu, J., Yan, P., Schatte, G. A., & Stadelmann, T. (2023) · IEEE Swiss Conference on Data Science (SDS) · doi:10.1109/sds57534.2023.00017 · Cited by 28 · see citing works

The Importance of Imaging Informatics and Informaticists in the Implementation of AI

Cook, T. S. (2019) · Academic Radiology · doi:10.1016/j.acra.2019.10.002 · Cited by 25 · see citing works

“Democratizing AI” and the Concern of Algorithmic Injustice

Lin, T.-A. (2024) · Philosophy & Technology · doi:10.1007/s13347-024-00792-2 · Cited by 21 · see citing works

The feasibility and inevitability of stealth attacks

Tyukin, I., Higham, D. J., Bastounis, A., Woldegeorgis, E., & Gorban, A. N. (2023) · IMA Journal of Applied Mathematics · doi:10.1093/imamat/hxad027 · Cited by 18 · see citing works

LEXI: Large Language Models Experimentation Interface

Laban, G., Laban, T., & Güneş, H. (2024) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3687272.3688296 · Cited by 16 · see citing works

ACR’s Connect and AI-LAB technical framework

Brink, L., Coombs, L. P., Veettil, D. K., Kuchipudi, K., Marella, S., Schmidt, K., Nair, S. S., Tilkin, M., Treml, C., Chang, K., et al. (2022) · JAMIA Open · doi:10.1093/jamiaopen/ooac094 · Cited by 17 · see citing works

Democratizing AI in public administration: improving equity through maximum feasible participation

Taylor, R. R., Murphy, J. W., Hoston, W. T., & Senkaiahliyan, S. (2024) · AI & Society · doi:10.1007/s00146-024-02120-w · Cited by 16 · see citing works

Democratising artificial intelligence in healthcare: community-driven approaches for ethical solutions

Welsh, C., García, S. R., Barnett, G. C., & Jena, R. (2024) · Future Healthcare Journal · doi:10.1016/j.fhj.2024.100165 · Cited by 12 · see citing works

Cardiovascular informatics: building a bridge to data harmony

Caufield, J. H., Sigdel, D., Fu, J., Choi, H., Guevara-Gonzalez, V., Wang, D., & Ping, P. (2021) · Cardiovascular Research · doi:10.1093/cvr/cvab067 · Cited by 11 · see citing works

From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care

Griffin, A. C., Topaloĝlu, Ü., Davis, S. R., & Chung, A. E. (2020) · Yearbook of Medical Informatics · doi:10.1055/s-0040-1701983 · Cited by 11 · see citing works

Color Shadows 2: Assessing the Impact of XAI on Diagnostic Decision-Making

Natali, C., Famiglini, L., Campagner, A., Maida, G. A. L., Gallazzi, E., & Cabitza, F. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-44064-9_33 · Cited by 10 · see citing works

On-Premise Artificial Intelligence as a Service for Small and Medium Size Setups

Fortuna, C., Mušić, D., Cerar, G., Čampa, A., Kapsalis, P., & Mohorčič, M. (2023) · Engineering cyber-physical systems and critical infrastructures · doi:10.1007/978-3-031-29301-6_3 · Cited by 10 · see citing works

AI Technicians: Developing Rapid Occupational Training Methods for a Competitive AI Workforce

Šavelka, J., Kültür, C., Agarwal, A., Bogart, C., Burte, H., Zhang, A., & Sakr, M. F. (2025) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3641554.3701935 · Cited by 11 · see citing works

Feature Management for Machine Learning Operation Pipelines in AI Native Networks

Cerar, G., Bertalanič, B., Mohorčič, M., Grobelnik, M., & Fortuna, C. (2023) · International Balkan Conference on Communications and Networking (BalkanCom) · doi:10.1109/balkancom58402.2023.10167936 · Cited by 5 · see citing works

A digital health trust framework guided by values from the science of yoga

Venkatasubramanian, A. (2023) · Oxford Open Digital Health · doi:10.1093/oodh/oqad007 · Cited by 4 · see citing works

Use of Medical Imaging to Advance Mental Health Care: Contributions from Neuroimaging Informatics

Gollub, R. L., & Benson, N. M. (2021) · Health informatics · doi:10.1007/978-3-030-70558-9_8 · Cited by 4 · see citing works

Legal implications of federated learning integration in digital healthcare systems

Imoize, A. L., Obaidat, M. S., & Song, H. H. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13897-3.00014-x · Cited by 3 · see citing works

Using Large Language Models for Medical Diagnosis: A Survey and Future Trends

Ashqar, R. I., Ashqar, A., Elehnawy, M., & Ashqar, H. I. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-15784-3_30 · Cited by 4 · see citing works

The potential for co-operatives to mitigate AI ethics catastrophes: perspectives from media analysis

Marino, D., & Moon, A. (2023) · IEEE International Symposium on Ethics in Engineering, Science, and Technology (ETHICS) · doi:10.1109/ethics57328.2023.10155081 · Cited by 1 · see citing works

Synthetic artificial intelligence in cardiology: from generative models to clinical applications

Parise, G., Ceravolo, R., Lucà, F., Gulizia, M. M., Tetta, C., Parise, O., Nardi, F., Grimaldi, M., & Gelsomino, S. (2026) · European Heart Journal Open · doi:10.1093/ehjopen/oeag026 · Cited by 1 · see citing works

Data Plateau: A Unified Analytics Platform with Intuitive Interfaces for Real-Time and ML-Driven Insights

Tasan, M., Ozkan, Y. A., Ozgur, A. O., & Özpınar, A. (2024) · Orclever Proceedings of Research and Development · doi:10.56038/oprd.v4i1.457 · Cited by 1 · see citing works

Natural Language Processing, or How to Communicate With Your Computer

Moreno, C. C. (2019) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2019.07.007

Osseous Tumors of the Bone

Pettit, W., Forster, D. A., Kransdorf, M. J., Murphey, M. D., Botchu, R., & Hegde, G. (2026) · Medical radiology · doi:10.1007/174_2026_684

Artificial Intelligence Democratization in Developing Economies through the Lenses of Small Business Operations

Nwosu, K. C., Westcott, S. C., Arachie, A. E., & Okafor, N. M. (2026) · African Journal of Management and Business Research · doi:10.62154/ajmbr.2026.022.01022

Accuracy of Descriptive and Illustrative Capacity of Generative Artificial Intelligence in Aesthetic Surgery: A Study of Accelerated Facial Aging in Depressed Medical Residents

Sultan, M. T., Sanan, M., Liu, W., & Li, G. (2026) · Aesthetic Plastic Surgery · doi:10.1007/s00266-026-05895-z

A People’s AI: Beyond Participation, Toward Genuine Democratization

Murphy, J. W., Taylor, R. R., & Lueras, M. A. (2026) · Philosophy & Technology · doi:10.1007/s13347-026-01116-2

A Human-Centered Web Technology for Reproducible Statistical and Machine-Learning Analysis of Heterogeneous Data

Vargas-Santiago, M., León-Velasco, D. A., García, S. Q., Ramírez, R. I. C., & Espinosa–Martínez, E.-G. (2026) · Technologies · doi:10.3390/technologies14100648

The Artificial Intelligence Ecosystem for the Radiological Sciences: Ideas to Clinical Practice

Allen, B., & Dreyer, K. (2018) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2018.02.032 · Cited by 14 · see citing works

When AI comes for your job: the radiology story

(n.d.) · Digital Repository Service (Northeastern University)

Artificial Intelligence in Imaging: The Radiologist’s Role

Rubin, D. L. (2019) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2019.05.036 · Cited by 110 · see citing works

AI for Radiology: A Primer Part I. From Idea to Algorithm

Tejani, A. S., Rauschecker, A. M., Kohli, M. D., & Mongan, J. (2025) · Radiology · doi:10.1148/radiol.250692 · Cited by 6 · see citing works

Letter From the Editor: Artificial Intelligence and Radiology

Agarwal, P. (2023) · Seminars in Roentgenology · doi:10.1053/j.ro.2023.01.007