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ORCIDAhmad P. Tafti
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2020 – today
- 2026
[j6]Jacob Thrasher, Alina Devkota, Prasiddha Siwakoti, Rohit Chivukula, Pranav Poudel, Chuanbo Hu, Ahmad P. Tafti, Binod Bhattarai, Prashnna Gyawali:
Multimodal Federated Learning in Healthcare: A Review. J. Heal. Informatics Res. 10(2): 419-448 (2026)- [c28]Fengyi Gao, Farnaz Rezvani
, Yushui Han, Michael Kann, Nickolas Littlefield, Hilal Maradit Kremers, Adolph J. Yates, Johannes F. Plate, Ahmad P. Tafti:
Uncertainty-Quantified and Explainable Age- and Sex-Aware Contrastive Learning for Knee Osteoarthritis Classification. ISBI 2026: 1-5 - [i8]Libing Kuang, Soren Salehi, Ziling Wu, Ahmad P. Tafti, Armaghan Moemeni:
Uni-Light: An Ultra-Lightweight Framework via Uncertainty-Aware Knowledge Distillation for Brain Tumour Segmentation. CoRR abs/2609.06729 (2026) - [i7]Jakir Hossain, Yi-Fei Zhao, Hongjian Wang, Minmei Shih, Katie Leigh Mullen, Ahmad P. Tafti, Leming Zhou, Manoj Purohit, William Hogan, Jay Zeng, Elizabeth Skidmore, Yanshan Wang:
Knowledge Graph-Augmented Ambient AI for Clinical Note Generation. CoRR abs/2609.22239 (2026) - 2025
- [j5]Soheyla Amirian, Fengyi Gao, Nickolas Littlefield, Jonathan H. Hill, Adolph J. Yates, Johannes F. Plate, Liron Pantanowitz, Hooman H. Rashidi, Ahmad P. Tafti:
State-of-the-Art in Responsible, Explainable, and Fair AI for Medical Image Analysis. IEEE Access 13: 58229-58263 (2025) - [j4]Tejasvi Sanjay Kamble, Hongtao Wang, Nicole Myers, Nickolas Littlefield, Leah Reid, Cynthia S. McCarthy, Young Ji Lee, Hongfang Liu, Liron Pantanowitz, Soheyla Amirian, Hooman H. Rashidi, Ahmad P. Tafti:
Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches. Int. J. Medical Informatics 197: 105822 (2025) - [c27]Behshid Behkamal, Amin Rezaei, Nickolas Littlefield, Samarth Bhardwaj, Leah Reid, Nicole Myers, Soheyla Amirian, Ahmad P. Tafti:
Explainable Feature Engineering in Health Data Science: Empirical Comparison of ChatGPT-4o and Classical Machine Learning Methods. CHASE 2025: 199-210 - [c26]Nickolas Littlefield, Michael Kann, Monjurul Islam, Maimouna Sanogo, Zoe Menezes, Fengyi Gao, Nicole Myers, Samuel Ewalefo, MaCalus V. Hogan, Johannes F. Plate, Qiangqiang Gu, Ahmad P. Tafti:
Self-supervised Representation Learning for AI-Based Musculoskeletal Radiograph Registry Construction. ISVC (1) 2025: 373-384 - 2024
- [j3]Nickolas Littlefield, Soheyla Amirian, Jacob T. Biehl, Edward G. Andrews, Michael Kann, Nicole Myers, Leah Reid, Adolph J. Yates, Brian J. McGrory, Bambang Parmanto, Thorsten M. Seyler, Johannes F. Plate, Hooman H. Rashidi, Ahmad P. Tafti:
Generative AI in orthopedics: an explainable deep few-shot image augmentation pipeline for plain knee radiographs and Kellgren-Lawrence grading. J. Am. Medical Informatics Assoc. 31(11): 2668-2678 (2024) - [c25]Mahbaneh Eshaghzadeh Torbati, Davneet S. Minhas, Ahmad P. Tafti, Charles DeCarli, Dana L. Tudorascu, Seong Jae Hwang:
ESPA: An Unsupervised Harmonization Framework via Enhanced Structure Preserving Augmentation. MICCAI (2) 2024: 184-194 - [c24]Jacob Thrasher, Alina Devkota, Ahmad P. Tafti, Binod Bhattarai, Prashnna K. Gyawali:
TE-SSL: Time and Event-Aware Self Supervised Learning for Alzheimer's Disease Progression Analysis. MICCAI (12) 2024: 324-333 - 2023
- [c23]Nickolas Littlefield, Johannes F. Plate, Kurt R. Weiss, Ines Lohse, Avani Chhabra, Ismaeel A. Siddiqui, Zoe Menezes, George M. Mastorakos, Sakshi Mehul Thakar, Mehrnaz Abedian, Matthew F. Gong, Luke A. Carlson, Hamidreza Moradi, Soheyla Amirian, Ahmad P. Tafti:
Learning Unbiased Image Segmentation: A Case Study with Plain Knee Radiographs. BHI 2023: 1-5 - [c22]Nickolas Littlefield, Hamidreza Moradi, Soheyla Amirian, Hilal Maradit Kremers, Johannes F. Plate, Ahmad P. Tafti:
Enforcing Explainable Deep Few-Shot Learning to Analyze Plain Knee Radiographs: Data from the Osteoarthritis Initiative. ICHI 2023: 252-260 - [c21]Nickolas Littlefield, Johannes F. Plate, Kurt R. Weiss, Ines Lohse, Avani Chhabra, Ismaeel A. Siddiqui, Zoe Menezes, George M. Mastorakos, Soheyla Amirian, Hamidreza Moradi, Ahmad P. Tafti:
AI Fairness in Hip Bony Anatomy Segmentation: Analyzing and Mitigating Gender and Racial Bias in Plain Radiography Analysis. ICHI 2023: 714-716 - [c20]Christina Letter, Puneet Gupta, Annie Kim, Guang-Ting Cong, Hongfang Liu, Ahmad P. Tafti:
Gender-Specific Machine Learning Models to Predict Unplanned Return to Operating Room Following Primary Total Shoulder Arthroplasty. ICHI 2023: 717-721 - [i6]Nickolas Littlefield, Johannes F. Plate, Kurt R. Weiss, Ines Lohse, Avani Chhabra, Ismaeel A. Siddiqui, Zoe Menezes, George M. Mastorakos, Sakshi Mehul Thakar, Mehrnaz Abedian, Matthew F. Gong, Luke A. Carlson, Hamidreza Moradi, Soheyla Amirian, Ahmad P. Tafti:
Learning Unbiased Image Segmentation: A Case Study with Plain Knee Radiographs. CoRR abs/2308.04356 (2023) - [i5]Soheyla Amirian, Luke A. Carlson, Matthew F. Gong, Ines Lohse, Kurt R. Weiss, Johannes F. Plate, Ahmad P. Tafti:
Explainable AI in Orthopedics: Challenges, Opportunities, and Prospects. CoRR abs/2308.04696 (2023) - 2022
- [c19]Soheyla Amirian, Husam Ghazaleh, Mehdi Assefi, Hilal Maradit Kremers, Hamid R. Arabnia, Johannes F. Plate, Ahmad P. Tafti:
Word Embedding Neural Networks to Advance Knee Osteoarthritis Research. CSCI 2022: 289-292 - [i4]Shi Yan, Taghi Ramazanian, Elham Sagheb, Walter K. Kremers, Vipin Chaudhary, Michael J. Taunton, Hilal Maradit Kremers, Ahmad P. Tafti:
Give me a knee radiograph, I will tell you where the knee joint area is: a deep convolutional neural network adventure. CoRR abs/2202.05382 (2022) - [i3]Soheyla Amirian, Husam Ghazaleh, Mehdi Assefi, Hilal Maradit Kremers, Hamid R. Arabnia, Johannes F. Plate, Ahmad P. Tafti:
Word Embedding Neural Networks to Advance Knee Osteoarthritis Research. CoRR abs/2212.11933 (2022) - 2020
- [j2]Yanshan Wang, Yiqing Zhao, Terry M. Therneau, Elizabeth J. Atkinson, Ahmad P. Tafti, Nan Zhang, Shreyasee Amin, Andrew H. Limper, Sundeep Khosla, Hongfang Liu:
Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records. J. Biomed. Informatics 102: 103364 (2020) - [c18]Luke A. Carlson, Jennifer St. Sauver, Sunyang Fu, Ahmad P. Tafti, Jungwei Fan, Molly M. Jeffery, Rozalina G. McCoy, Hongfang Liu, Yanshan Wang:
Big Impact from Small Data: Unsupervised Machine Learning Approaches for Chronic Pain Patient Subgrouping. AMIA 2020 - [c17]Shi Yan, Taghi Ramazanian, Elham Sagheb, Sunyang Fu, Sunghwan Sohn, David G. Lewallen, Hongfang Liu, Walter K. Kremers, Vipin Chaudhary, Michael J. Taunton, Hilal Maradit Kremers, Ahmad P. Tafti:
DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. ISVC (2) 2020: 154-165
2010 – 2019
- 2019
- [c16]Ahmad P. Tafti, Edin Cubro, Hongfang Liu, Brian W. Pickering, Vitaly Herasevich:
Privacy-preserving and non-intrusive video recognition technique to count the number of patient room visits during patient deterioration: a simulation study. AMIA 2019 - [c15]Maryam Zolnoori, Che Ngufor, Anthony Faiola, Christina Eldredge, Jake Luo, Sunghwan Sohn, Joyce E. Balls-Berry, Ahmad P. Tafti, Nilay D. Shah, Timothy B. Patrick:
Identifying Factors Affecting Drug Discontinuation in Patients with Depression: Text Analysis of Patient Drug Review Posts. AMIA 2019 - [c14]Ahmad P. Tafti, Yanshan Wang, Feichen Shen, Elham Sagheb, Paul R. Kingsbury, Hongfang Liu:
Integrating word embedding neural networks with PubMed abstracts to extract keyword proximity of chronic diseases. BHI 2019: 1-4 - [c13]Ahmad P. Tafti, Sunyang Fu, Aditya Khurana, George M. Mastorakos, Kenneth G. Poole, Stephen J. Traub, James A. Yiannias, Hongfang Liu:
Artificial intelligence to organize patient portal messages: a journey from an ensemble deep learning text classification to rule-based named entity recognition. BIBM 2019: 1380-1387 - [c12]Ahmad P. Tafti, Yue Dong, Elizabeth B. Habermann, Hongfang Liu, Vitaly Herasevich:
Relationship Between Very Cold Outside Weather and Surgical Outcome: Integrating Shallow and Deep Artificial Neural Nets. MedInfo 2019: 1783-1784 - [c11]Yanshan Wang, Ahmad P. Tafti, Sunghwan Sohn, Rui Zhang:
Applications of Natural Language Processing in Clinical Research and Practice. NAACL-HLT (Tutorial Abstracts) 2019: 22-25 - [i2]Yanshan Wang, Yiqing Zhao, Terry M. Therneau, Elizabeth J. Atkinson, Ahmad P. Tafti, Nan Zhang, Shreyasee Amin, Andrew H. Limper, Hongfang Liu:
Unsupervised Machine Learning for the Discovery of Latent Disease Clusters and Patient Subgroups Using Electronic Health Records. CoRR abs/1905.10309 (2019) - 2018
- [j1]Ahmad Pahlavan Tafti, Ahmadreza Baghaie, Andrew B. Kirkpatrick, Jessica D. Holz, Heather A. Owen, Roshan M. D'Souza, Zeyun Yu:
A comparative study on the application of SIFT, SURF, BRIEF and ORB for 3D surface reconstruction of electron microscopy images. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 6(1): 17-30 (2018) - [c10]Ahmad Pahlavan Tafti, Fereshteh S. Bashiri, Eric LaRose, Peggy L. Peissig:
Diagnostic Classification of Lung CT Images Using Deep 3D Multi-Scale Convolutional Neural Network. ICHI 2018: 412-414 - [c9]Yirong Wu, Jun Fan, Peggy L. Peissig, Richard L. Berg, Ahmad Pahlavan Tafti, Jie Yin, Ming Yuan, David Page, Jennifer Cox, Elizabeth S. Burnside:
Quantifying predictive capability of electronic health records for the most harmful breast cancer. Image Perception, Observer Performance, and Technology Assessment 2018: 105770J - 2017
- [c8]Mehdi Assefi, Ehsun Behravesh, Guangchi Liu, Ahmad Pahlavan Tafti:
Big data machine learning using apache spark MLlib. IEEE BigData 2017: 3492-3498 - [c7]Ahmad Pahlavan Tafti, Ehsun Behravesh, Mehdi Assefi, Eric LaRose, Jonathan C. Badger, John Mayer, AnHai Doan, David Page, Peggy L. Peissig:
bigNN: An open-source big data toolkit focused on biomedical sentence classification. IEEE BigData 2017: 3888-3896 - [c6]Ahmad Pahlavan Tafti, Eric LaRose, Jonathan C. Badger, Ross Kleiman, Peggy L. Peissig:
Machine Learning-as-a-Service and Its Application to Medical Informatics. MLDM 2017: 206-219 - 2016
- [c5]Ahmad Pahlavan Tafti, Ahmadreza Baghaie, Mehdi Assefi, Hamid R. Arabnia, Zeyun Yu, Peggy L. Peissig:
OCR as a Service: An Experimental Evaluation of Google Docs OCR, Tesseract, ABBYY FineReader, and Transym. ISVC (1) 2016: 735-746 - 2015
- [c4]Ahmad Pahlavan Tafti, Hamid Hassannia, Dee Piziak, Zeyun Yu:
SeLibCV: A Service Library for Computer Vision Researchers. ISVC (2) 2015: 542-553 - [c3]Mengyuan Zhao, Heng Luo, Ahmad Pahlavan Tafti, Yuanchang Lin, Guotian He:
A Hybrid Real-Time Visual Tracking Using Compressive RGB-D Features. ISVC (1) 2015: 561-573 - [i1]Ahmad Pahlavan Tafti, Hamid Hassannia, Zeyun Yu:
siftservice.com - Turning a Computer Vision algorithm into a World Wide Web Service. CoRR abs/1504.02840 (2015) - 2014
- [c2]Ahmad Pahlavan Tafti, Andrew B. Kirkpatrick, Heather A. Owen, Zeyun Yu:
3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches. ISVC (2) 2014: 141-152 - 2012
- [c1]Mohammad V. Malakooti, Ahmad Pahlavan Tafti, Hamid Reza Naji:
An efficient algorithm for human cell detection in electron microscope images based on cluster analysis and vector quantization techniques. DICTAP 2012: 125-129
Coauthor Index
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last updated on 2026-10-14 00:50 CEST by the dblp team
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