Privacy-preserving and non-intrusive video recognition technique to count the number of patient room visits during patient deterioration: a simulation study. - Ahmad P. Tafti; Edin Cubro; Hongfang Liu; Brian W. Pickering; Vitaly Herasevich (AMIA, 2019)

Identifying Factors Affecting Drug Discontinuation in Patients with Depression: Text Analysis of Patient Drug Review Posts. - 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 (AMIA, 2019)

Integrating word embedding neural networks with PubMed abstracts to extract keyword proximity of chronic diseases. - Ahmad P. Tafti; Yanshan Wang; Feichen Shen; Elham Sagheb; Paul R. Kingsbury; Hongfang Liu (BHI, 2019)

Artificial intelligence to organize patient portal messages: a journey from an ensemble deep learning text classification to rule-based named entity recognition. - Ahmad P. Tafti; Sunyang Fu; Aditya Khurana; George M. Mastorakos; Kenneth G. Poole; Stephen J. Traub; James A. Yiannias; Hongfang Liu (BIBM, 2019)

Relationship Between Very Cold Outside Weather and Surgical Outcome: Integrating Shallow and Deep Artificial Neural Nets. - Ahmad P. Tafti; Yue Dong 003; Elizabeth B. Habermann; Hongfang Liu; Vitaly Herasevich (MedInfo, 2019)

Applications of Natural Language Processing in Clinical Research and Practice. - Yanshan Wang; Ahmad P. Tafti; Sunghwan Sohn; Rui Zhang (NAACL-HLT (Tutorial Abstracts), 2019)

Unsupervised Machine Learning for the Discovery of Latent Disease Clusters and Patient Subgroups Using Electronic Health Records. - Yanshan Wang; Yiqing Zhao; Terry M. Therneau; Elizabeth J. Atkinson; Ahmad P. Tafti; Nan Zhang; Shreyasee Amin; Andrew H. Limper; Hongfang Liu (CoRR, 2019)

Big Impact from Small Data: Unsupervised Machine Learning Approaches for Chronic Pain Patient Subgrouping. - Luke A. Carlson; Jennifer St. Sauver; Sunyang Fu; Ahmad P. Tafti; Jungwei Fan 001; Molly M. Jeffery; Rozalina G. McCoy; Hongfang Liu; Yanshan Wang (AMIA, 2020)

DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. - 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 (ISVC (2), 2020)

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records. - Yanshan Wang; Yiqing Zhao; Terry M. Therneau; Elizabeth J. Atkinson; Ahmad P. Tafti; Nan Zhang; Shreyasee Amin; Andrew H. Limper; Sundeep Khosla; Hongfang Liu (J. Biomed. Informatics, 2020)

Word Embedding Neural Networks to Advance Knee Osteoarthritis Research. - Soheyla Amirian; Husam Ghazaleh; Mehdi Assefi; Hilal Maradit Kremers; Hamid R. Arabnia; Johannes F. Plate; Ahmad P. Tafti (CSCI, 2022)

Give me a knee radiograph, I will tell you where the knee joint area is: a deep convolutional neural network adventure. - Shi Yan; Taghi Ramazanian; Elham Sagheb; Walter K. Kremers; Vipin Chaudhary; Michael J. Taunton; Hilal Maradit Kremers; Ahmad P. Tafti (CoRR, 2022)

Learning Unbiased Image Segmentation: A Case Study with Plain Knee Radiographs. - 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; et al. (BHI, 2023)

Gender-Specific Machine Learning Models to Predict Unplanned Return to Operating Room Following Primary Total Shoulder Arthroplasty. - Christina Letter; Puneet Gupta; Annie Kim; Guang-Ting Cong; Hongfang Liu; Ahmad P. Tafti (ICHI, 2023)

Enforcing Explainable Deep Few-Shot Learning to Analyze Plain Knee Radiographs: Data from the Osteoarthritis Initiative. - Nickolas Littlefield; Hamidreza Moradi; Soheyla Amirian; Hilal Maradit Kremers; Johannes F. Plate; Ahmad P. Tafti (ICHI, 2023)

AI Fairness in Hip Bony Anatomy Segmentation: Analyzing and Mitigating Gender and Racial Bias in Plain Radiography Analysis. - 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 (ICHI, 2023)

Explainable AI in Orthopedics: Challenges, Opportunities, and Prospects. - Soheyla Amirian; Luke A. Carlson; Matthew F. Gong; Ines Lohse; Kurt R. Weiss; Johannes F. Plate; Ahmad P. Tafti (CoRR, 2023)

TE-SSL: Time and Event-Aware Self Supervised Learning for Alzheimer's Disease Progression Analysis. - Jacob Thrasher; Alina Devkota; Ahmad P. Tafti; Binod Bhattarai; Prashnna K. Gyawali (MICCAI (12), 2024)

ESPA: An Unsupervised Harmonization Framework via Enhanced Structure Preserving Augmentation. - Mahbaneh Eshaghzadeh Torbati; Davneet S. Minhas; Ahmad P. Tafti; Charles DeCarli; Dana L. Tudorascu; Seong Jae Hwang (MICCAI (2), 2024)

Generative AI in orthopedics: an explainable deep few-shot image augmentation pipeline for plain knee radiographs and Kellgren-Lawrence grading. - 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; et al. (J. Am. Medical Informatics Assoc., 2024)

State-of-the-Art in Responsible, Explainable, and Fair AI for Medical Image Analysis. - Soheyla Amirian; Fengyi Gao; Nickolas Littlefield; Jonathan H. Hill; Adolph J. Yates; Johannes F. Plate; Liron Pantanowitz; Hooman H. Rashidi; Ahmad P. Tafti (IEEE Access, 2025)

Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches. - 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 (Int. J. Medical Informatics, 2025)