Institution · Artificial Intelligence in Medicine (Canada)
Most cited papers from Artificial Intelligence in Medicine (Canada)
What are the most cited papers from Artificial Intelligence in Medicine (Canada)?
The most cited paper from Artificial Intelligence in Medicine (Canada) is "Efficient Graph-Based Image Segmentation" (Pedro F. Felzenszwalb, Daniel P. Huttenlocher, 2004), with 6,257 citations. Next come "Pictorial Structures for Object Recognition" (2,222) and "Evolution of genes and genomes on the Drosophila phylogeny" (2,132).
Showing 50 of 61 papers. Every paper with more than 216 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Efficient Graph-Based Image Segmentation Pedro F. Felzenszwalb, Daniel P. Huttenlocher · International Journal of Computer Vision | 31 Mar 2004 | 6,257 |
| 2 | Pictorial Structures for Object Recognition Pedro F. Felzenszwalb, Daniel P. Huttenlocher · International Journal of Computer Vision | 27 Sep 2004 | 2,222 |
| 3 | Evolution of genes and genomes on the Drosophila phylogeny Andrew G. Clark et al. · Nature | Nov 2007 | 2,132 |
| 4 | Diagnosing multiple faults Johan de Kleer, Brian C. Williams · Artificial Intelligence | Apr 1987 | 2,053 |
| 5 | Planning for conjunctive goals David Chapman · Artificial Intelligence | Jul 1987 | 1,114 |
| 6 | CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection Abdul Waheed, Muskan Goyal, Deepak Kumar Gupta et al. · IEEE Access | 2020 | 780 |
| 7 | Adapted large language models can outperform medical experts in clinical text summarization Dave Van Veen, Cara Van Uden, Louis Blankemeier et al. · Nature Medicine | 27 Feb 2024 | 761 |
| 8 | Applications of Deep Learning in Biomedicine Polina Mamoshina, Armando S. Vieira, Eugene Lane et al. · Molecular Pharmaceutics | 23 Mar 2016 | 723 |
| 9 | ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional networks Abhijit Guha Roy, Sailesh Conjeti, Sri Phani Krishna Karri et al. · Biomedical Optics Express | 13 Jul 2017 | 626 |
| 10 | Bilateral Filtering: Theory and Applications Sylvain Paris, Pierre Kornprobst, Jack Tumblin et al. · Foundations and Trends® in Computer Graphics and Vision | 20 Aug 2009 | 585 |
| 11 | Fast optimal leaf ordering for hierarchical clustering Ziv Bar‐Joseph, David K. Gifford, Tommi Jaakkola · Bioinformatics | Jun 2001 | 581 |
| 12 | TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP John X. Morris, Eli Lifland, Jin Yong Yoo et al. | 2020 | 552 |
| 13 | The TRIPOD-LLM reporting guideline for studies using large language models Jack Gallifant et al. · Nature Medicine | 2025 | 517 |
| 14 | Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos Devamanyu Hazarika, Soujanya Poria, Amir Zadeh et al. | 2018 | 477 |
| 15 | Cutting the Gordian Knot: The Moving-Average Type–Token Ratio (MATTR) Michael A. Covington, Joe D. McFall · Journal of Quantitative Linguistics | May 2010 | 471 |
| 16 | Self-supervised learning for medical image classification: a systematic review and implementation guidelines Shih-Cheng Huang, Anuj Pareek, Malte Jensen et al. · npj Digital Medicine | 26 Apr 2023 | 462 |
| 17 | The Michigan Internet AuctionBot Peter R. Wurman, Michael P. Wellman, William E. Walsh | 1998 | 459 |
| 18 | Description and recognition of curved objects☆ Ramakant Nevatia, Thomas O. Binford · Artificial Intelligence | Feb 1977 | 451 |
| 19 | S2ORC: The Semantic Scholar Open Research Corpus Kyle Lo, Lucy Lu Wang, Mark E Neumann et al. | 2020 | 446 |
| 20 | On Detecting Edges Vishvjit S. Nalwa, Thomas O. Binford · IEEE Transactions on Pattern Analysis and Machine Intelligence | Nov 1986 | 436 |
| 21 | Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative Charlene Ronquillo, Laura‐Maria Peltonen, Lisiane Pruinelli et al. · Journal of Advanced Nursing | 18 May 2021 | 434 |
| 22 | Artificial intelligence in radiation oncology Elizabeth Huynh, Ahmed Hosny, Christian V. Guthier et al. · Nature Reviews Clinical Oncology | 25 Aug 2020 | 420 |
| 23 | fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning Florian Johannes Knoll et al. · Radiology Artificial Intelligence | 2020 | 419 |
| 24 | Fuzzy real algebra: Some results Didier Dubois, Henri M. Prade · Fuzzy Sets and Systems | Oct 1979 | 410 |
| 25 | A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence Zeynep Akata et al. · Computer | 31 Jul 2020 | 398 |
| 26 | "One size fits all": an idea whose time has come and gone Michael R Stonebraker, U. Cetintemel | 2005 | 390 |
| 27 | Mixed Transformer U-Net for Medical Image Segmentation Hongyi Wang, Shiao Xie, Lanfen Lin et al. · ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | 27 Apr 2022 | 381 |
| 28 | The genetic prehistory of southern Africa Joseph K. Pickrell et al. · Nature Communications | 16 Oct 2012 | 376 |
| 29 | Image Analysis Using Multigrid Relaxation Methods Demetri Terzopoulos · IEEE Transactions on Pattern Analysis and Machine Intelligence | Mar 1986 | 372 |
| 30 | Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation Yifan Feng, Jiangang Huang, Shaoyi Du et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 30 Dec 2024 | 363 |
| 31 | ChatGPT in healthcare: A taxonomy and systematic review Jianning Li, Amin Dada, Behrus Puladi et al. · Computer Methods and Programs in Biomedicine | 21 Jan 2024 | 359 |
| 32 | Model-Based Three-Dimensional Interpretations of Two-Dimensional Images Rodney A. Brooks · IEEE Transactions on Pattern Analysis and Machine Intelligence | Mar 1983 | 359 |
| 33 | Organoid Cultures as Preclinical Models of Non–Small Cell Lung Cancer Ruoshi Shi, Nikolina Radulovich, Christine Ng et al. · Clinical Cancer Research | 6 Nov 2019 | 333 |
| 34 | Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study Anindo Saha et al. · The Lancet Oncology | 12 Jun 2024 | 332 |
| 35 | Design, kinematics, and control of a soft spatial fluidic elastomer manipulator Andrew D. Marchese, Daniela L. Rus · The International Journal of Robotics Research | 6 Oct 2015 | 332 |
| 36 | Impact of a deep learning assistant on the histopathologic classification of liver cancer Amirhossein Kiani et al. · npj Digital Medicine | 26 Feb 2020 | 329 |
| 37 | An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization W. Eric L. Grimson, Gil J. Ettinger, Steve White et al. · IEEE Transactions on Medical Imaging | Apr 1996 | 320 |
| 38 | Material perception: What can you see in a brief glance? L. Sharan, Ruth E. Rosenholtz, Edward H. Adelson · Journal of Vision | 4 Jun 2010 | 318 |
| 39 | Omega-3 Fatty Acids for Major Depressive Disorder During Pregnancy Kuan‐Pin Su, Shih‐Yi Huang, Tsan-Hung Chiu et al. · The Journal of Clinical Psychiatry | 15 Apr 2008 | 303 |
| 40 | Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction Salah S. Al‐Zaiti, Christian Martin‐Gill, Jessica K. Zègre‐Hemsey et al. · Nature Medicine | 29 Jun 2023 | 302 |
| 41 | Computations underlying the measurement of visual motion Ellen C. Hildreth · Artificial Intelligence | Aug 1984 | 302 |
| 42 | Estimation of the Transmission Risk of 2019-nCov and Its Implication for Public Health Interventions (2019-nCov的传播风险估计及其对公共卫生干预的意义) Biao Tang, Xia Wang, Qian Li et al. · SSRN Electronic Journal | 2020 | 301 |
| 43 | Fine-Grained Analysis of Propaganda in News Article Giovanni Da San Martino, Seunghak Yu, Alberto Barrón‐Cedeño et al. | 2019 | 288 |
| 44 | Large language models to identify social determinants of health in electronic health records Marco Fidel Guevara-Vega, Shan Chen, Spencer A. Thomas et al. · npj Digital Medicine | 10 Jan 2024 | 287 |
| 45 | What do Neural Machine Translation Models Learn about Morphology? Yonatan Belinkov, Nadir Durrani, Fahim Dalvi et al. | 2017 | 287 |
| 46 | QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab et al. · NeuroImage | 29 Nov 2018 | 265 |
| 47 | Deep learning classification of lung cancer histology using CT images Tafadzwa Lawrence Chaunzwa, Ahmed Hosny, Yiwen Xu et al. · Scientific Reports | 9 Mar 2021 | 257 |
| 48 | Acidification of Tumor at Stromal Boundaries Drives Transcriptome Alterations Associated with Aggressive Phenotypes Nazanin Rohani, Liangliang Hao, Maria S. Alexis et al. · Cancer Research | 12 Feb 2019 | 257 |
| 49 | Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection Shih-Cheng Huang, Anuj Pareek, Roham T. Zamanian et al. · Scientific Reports | 17 Dec 2020 | 255 |
| 50 | Reinforcement learning for mapping instructions to actions S. R. K. Branavan, Harr Chen, Luke Zettlemoyer et al. | 2009 | 255 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.