2025 publications

• T. Syeda-Mahmood, K.C.L. Wong, S. Kashyap, N Dsouza, L. Shi, R. Mahmood, H. Wang, “SemCLIP: A semantic memory-aligned vision language model,” in Proc. Machine Learning Research (PMLR) Journal, Also in NeurIPS, UniReps Workshop on Unified Representations, Dec. 6 2025.
• R. Mahmood, P. Yan, Tanveer Syeda-Mahmood, “Automatic Correction of AI Reports using Fact-Checking Model-guided LLMs,” in Proc. NeurIPS Workshop on GenAI for Health: Potential, Trust, and Policy Compliance, Dec. 6, 2025.
• H. Wang and T. Syeda-Mahmood, “Vector data search with sorting transformation,” in ICML Workshop on Vector Databases, Vancouver, July 18, 2025.
• R. Mahmood, Diego Machado-Reyes, Joy Wu, Parisa Kaviani, Ken C.L. Wong, Niharika D'Souza, Mannudeep Kalra, Ge Wang, Pingkun Yan, Tanveer Syeda-Mahmood, “Phrase-grounded Fact-checking for Automatically Generated Chest X-ray Reports,” in Proc. Medical Imaging and Computer-Assisted Intervention (MICCAI), 2025.
• R. Mahmood, D. Machado-Reyes, J. Wu, P. Kaviani, Ken C.L. Wong, N. D'Souza, M. Kalra, Ge Wang, P. Yan, Tanveer Syeda-Mahmood, “Evaluating automated radiology report quality through fine-grained phrasal ground of clinical findings ” in IEEE ISBI, Apr. 2025.

2024 publications

• R. Bonazzola, E. Ferrante, N. Ravikumar, Y. Xia, B. Keavney, S. Plein, T. Syeda-Mahmood, and A. F Frangi, “Unsupervised ensemble-based phenotyping enhances gene discoverability in imaging genetics: new associations from left-ventricular morphology,” in Nature Machine Intelligence, 6(3):291-306, March 2024, IF=23.8.
• E. Warner, J. Lee, W. Hsu, T. Syeda-Mahmood, C. E. Kahn, O. Gevaert, A. Rao, “Multimodal Machine Learning in Image-Based and Clinical Biomedicine: Survey and Prospects,” in International Journal of Computer Vision (IJCV), April 2024, IF=19.5
• E. Katsoulakis, Qi Wang, H. Wu, L. Shahriyari, R. Fletcher, J. Liu, L. Achenie, H. Liu, P. Jackson, Y. Xiao, T. Syeda-Mahmood, R. Tuli, J. Deng, "Digital twins for health: a scoping review,", NPJ Digital Medicine, vol.7, 77, 2024. IF=15.35
• V. Subramanian, T. Syeda-Mahmood, M.N. Do, "Modelling-based joint embedding of histology and genomics using canonical correlation analysis for breast cancer survival prediction," in Artificial Intelligence in Medicine, Mar:149:102787, 2024, IF=14.0
• N.S. DSouza, H. Wang, A. Giovannini, A. Foncubierta-Rodriguez, K. L. Beck, O. Boyko, T. Syeda-Mahmood, "Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction from Medical Data and Beyond", Medical Image Analysis Journal, January 2024. IF=10.9
• H. Wang, and T. Syeda-Mahmood, “Vector quantization with sorting transformation,” in IEEE International Conference on Big Data, Washington, D.C., Dec. 2024. Also in NeurIPS Workshop on Compression, Vancouver, Dec. 2024.
• S. Kashyap, N Dsouza, L. Shi, K.C.L. Wong, H. Wang, T. Syeda-Mahmood, “Modern Hopfield Networks meet Encoded Neural Representations – Addressing Practical Considerations,” in TMLR and NeuIPS 2024 UniReps Workshop, 2024.
• Singh SB, Wang H, Baratto L, Wu JT, Vasyliv I, Adams L, Sarrami AH, Syeda-Mahmood T, Daldrup‐Link H.E. Deep Learning Algorithm for Automatic Pediatric Lymphoma Detection Using Multimodal FDG PET/MRI Images. Society for Pediatric Radiology (SPR) 2024, Supplement 2024.
• Y. Chen, N. D’Souza, A. Mandepally, P. Henninger, S. Kashyap, N. Karani, N, Dey, M. Zachary, R. Rizq, P. Chouinard, P. Golland, T. Syeda-Mahmood, “Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound,” in Proc. Machine Learning for Medical Imaging (MLMI) Workshop, MICCAI 2024.
• H. Wang, A. Sarrami, J. T. Wu, L. Baratto, A. Sharma, K. C L Wong, S. B. Singh, H. E Daldrup-Link, T. Syeda-Mahmood, "Multimodal Pediatric Lymphoma Detection using PET and MRI," in Proc. AMIA Annual Symposium, Jan. 2024.

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2023 publications

• H. Wang, S. Kashyap, N. D'Souza, T. Syeda-Mahmood, "Statistics-guided Associative Memories," in NeurIPS Workshop on Associative Memory and Hopfield Networks, Dec. 2023.
• S. Kashyap, N. Karani, A. Shang, N, D’Souza, N. Dey, L. Jain, R. Wang, H. Akakin, D. Li, W. Li, C. Carlson, P. Golland, T. Syeda-Mahmood, “Feature selection for malapposition detection in intravascular ultrasound – A comparative study,” in Proc. Applications of Artificial Intelligence Workshop, MICCAI 2023, Vancouver, BC, pp. 165-178. 2023.
• Ken C. L. Wong, Hongzhi Wang, Tanveer Syeda-Mahmood, “HartleyMHA: Self-Attention in Frequency Domain for Resolution-Robust and Parameter-Efficient 3D Image Segmentation”, in International Conference of Medical Image Computing and Computer-Assisted Intervention, MICCAI, 2023.
• Hongzhi Wang, Amirhossein Sarrami, Joy Tzung-yu Wu, Lucia Baratto, Arjun Sharma, Ken C. L. Wong, Shashi Bhushan Singh, Heike E Daldrup-Link, Tanveer Syeda-Mahmood, “Multimodal Pediatric Lymphoma Detection using PET and MRI”, in AMIA 2023 Annual Symposium, 2023.
• Ken C. L. Wong, Hongzhi Wang, and Tanveer Syeda-Mahmood, “FNOSeg3D: resolution-robust 3D image segmentation with Fourier neural operator,” in IEEE International Symposium on Biomedical Imaging, ISBI 2023.

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2022 publications

• Stahlberg, E.A., Abdel-Rahman, M., Aguilar, B., Asadpoure, A., Beckman, R.A., Borkon, L.L., Bryan, J.N., Cebulla, C.M., Chang, Y.H., Chatterjee, A. and Deng, J., 2022. Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation. Frontiers in Digital Health, 4, p.1007784. 2022, (IF=3.2)
• Syeda-Mahmood, Tanveer, and Luyao Shi. "Searching for Fine-Grained Queries in Radiology Reports Using Similarity-Preserving Contrastive Embedding." In Jl. Of Machine Learning Research, vol.182:1–15, 2022. (IF=4.09)
• N. D'Souza, H. Wang, A. Giovannini, A. Foncubierta-Rodríguez, K. Beck, O. Boyko, T. Syeda-Mahmood, “Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis,” in Proc. MICCAI 2022. MICCAI Young Scientist Award Finalist.
• A. Jadhav, M. Moradi. S. Kashyap, T. Syeda-Mahmood, “Towards Automatic Prediction of Outcome in Treatment of Cerebral Aneurysms,” in Proc. AMIA 2022.
• N. Srivathsa, R. Mahmood, T. Syeda-Mahmood, “Spatially preserving flattening for location-aware classification of findings in chest X-rays,” in Proc. ISBI 2022.

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2021 publications

• Hernandez-Boussard, Tina, Paul Macklin, Emily J. Greenspan, Amy L. Gryshuk, Eric Stahlberg, Tanveer Syeda-Mahmood, and Ilya Shmulevich. "Digital twins for predictive oncology will be a paradigm shift for precision cancer care", Nature Medicine, vol. 27, no. 12 (2021): 2065-2066. (IF=87.8) (Commentary)
• L. Shi, T. Syeda-Mahmood, T. Baldwin, “Improving Neural Models for Radiology Report Retrieval with Lexicon-based Automated Annotation,” in Proc. 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), 2022.
• R. Bonazzola, N. Ravikumar, R. Attar, E. Ferrante, T. Syeda-Mahmood, A. F. Frangi, “Image-derived phenotype extraction for genetic discovery via unsupervised deep learning in CMR images,” in Proc. MICCAI 2021.
• V. Subramanian, T. Syeda-Mahmood, Minh N. Do, “Multimodal fusion using sparse CCA for breast cancer survival prediction, IEEE ISBI 2021.
• H. Wang. V. Subramanian, T. Syeda-Mahmood, Modeling uncertainty in multimodal fusion for lung cancer survival analysis, IEEE ISBI 2021.
• K. C. L. Wong, E. S. Sinkovskaya, M.D., A. Z. Abuhamad, M.D., T. Syeda-Mahmood, “Multiview and Multiclass Image Segmentation using Deep Learning in Fetal Echocardiography,” in Proc. SPIE Medical Imaging 2021.
• A. Jadhav, T. Baldwin, J. Wu, V. Mukherjee, T. Syeda-Mahmood, “Semantic Expansion of Clinician Generated Data Preferences for Automatic Patient Data Summarization”, AMIA 2021.

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2020 publications

• Tanveer Syeda-Mahmood, Ken C. L. Wong, Joy T. Wu, Ashutosh Jadhav, Orest Boyko, Extracting and Learning Fine-grained Labels from Chest Radiographs, AMIA Annual Symposium, (AMIA) 2020. Won the Homer Warner Award for outstanding contribution to the field of biomedical informatics.
• J. Wu, K. C. L. Wong, Y. Gur, N. Ansari, A. Karargyris, A.Sharma, M. Morris, B. Sabury, H. Ahmad, O. Boyko, A. Syed, A. Jadhav, H. Wang, A. Pillai, S. Kashyap, M. Moradi, T. Syeda-Mahmood, "Artificial Intelligence versus Entry-level Radiologists for Full-fledged Preliminary Read of Frontal AP Chest Radiographs: A Comparative Study", Journal of American Medical Informatics Association, (JAMA) Network, October 9, 2020.
• T. Syeda-Mahmood, K. C. L. Wong, Y. Gur, J. T. Wu, Ashutosh Jadhav, A. Karargyris, A. Pillai, A. Sharma, A. Syed, O. Boyko, M. Moradi, "Chest X-ray Report Generation through fine-grained label learning," in Proc. Medical Imaging and Computer-Assisted Interaction, pp.561-571, (MICCAI 2020).
• A. Jadhav, K. C. L. Wong, J. Wu, M. Moradi, T. Syeda-Mahmood. "Combining Deep Learning and Knowledge-driven Reasoning for Chest X-Ray Findings Detection" in Proc. American Medical Informatics Association Annual Symposium 2020 (AMIA 2020).
• J. T. Wu, A. Syed, H. Ahmad, A. Pillai, Y. Gur, A. Jadhav, D. Gruhl, L. Kato, M. Moradi, T. Syeda-Mahmood, “AI Accelerated Human-in-the-loop Structuring of Radiology Reports,” AMIA Annual Symposium 2020.
• K. C. L. Wong, M. Moradi, J. Wu, A. Pillai, A. Sharma, Y. Gur, H. Ahmad, M. S. l Chowdary, J. Chiranjeevi, K. K. Reddy P., W. Venkateswar, D. C Reddy, T. Syeda-Mahmood, "A robust network architecture to detect normal chest X-ray radiographs," in Proc. (ISBI) 2020.
• Karina Kanjaria, Anup Pillai, Chaitanya Shivade, Marina Bendersky, Vandana Mukherjee and Tanveer Syeda-Mahmood, “Receptivity of an AI Cognitive Assistant by the Radiology Community: A Report on Data Collected at RSNA,” Best Industrial Paper Award at International Conference on Healthcare Informatics (part of BIOSTEC 2020).
• J. T. Wu, Y. Gur, A. Karargyris, A.B. Syed, O. Boyko, M. Moradi, T. Syeda-Mahmood, "Automatic Bounding Box Annotation of Chest X-Ray Data for Localization of Abnormalities," in Proc. ISBI 2020.
• S. Kashyap, A. Karargyris, Joy T. Wu, Y. Gur, A. Sharma, K. C.L. Wong, M. Moradi, T. Syeda-Mahmood, "Looking in the Right Place for Anomalies: Explainable AI Through Automatic Location Learning," in Proc. ISBI 2020.
• V. Subramanian, M. Do, T. Syeda-Mahmood, "Multimodal Fusion of Imaging and Genomics for Lung Cancer Recurrence Prediction," in Proc. ISBI 2020
• J. Francis, H. Wang, K. White, T. Syeda-Mahmood, R. Stevens, "Neural Network Segmentation of Cell Ultrastructure Using Incomplete Annotation," in Proc. ISBI 2020.
• M. Moradi, K. C. L. Wong, A. Karargyris, and T. Syeda-Mahmood, "Quality controlled segmentation to aid disease detection", in SPIE Medical Imaging 2020.

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2019 publications

• E. Greenspan, C. Lauzon, A. Gryshuk, J. Ozik, N Collier, T. Syeda-Mahmood, I. Shmulevich, T. Hernandez-Boussard, P. Macklin, “Digital Twins for Predictive Cancer Care: an HPC-Enabled Community Initiative,” in Proc. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Nov. 18-21, 2019.
• A. Karargyris, K. C. L. Wong, Joy T Wu, M. Moradi, T. Syeda-Mahmood, "Boosting the rule-out accuracy of deep disease detection using class weight modifiers", IEEE ISBI 2019.
• T. Syeda-Mahmood, H. M Ahmad, N. Ansari, Yaniv Gur, Satyananda Kashyap, Alexandros Karargyris, Mehdi Moradi, Anup Pillai, Karthik Sheshadri, Weiting Wang, Ken CL Wong, Joy T Wu, "Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays", IEEE ISBI 2019.
• A. Harouni, H. Wang, T. Syeda-Mahmood, David Beymer, "Deep Network Anatomy Segmentation with Limited Annotations Using Auxiliary Labels", IEEE ISBI 2019.
• S. Kashyap, M. Moradi, A. Karargyris, Joy T Wu, M. Morris, B. Saboury, E. Siegel, T. Syeda-Mahmood, “Artificial Intelligence for Point of Care Radiograph Quality Assessment”, SPIE Medical Imaging 2019.
• C. Agunwa, Mehdi Moradi, Ken C.L. Wong, T. Syeda-Mahmood, “Body Part and Imaging Modality Classification for a General Radiology Cognitive Assistant”, SPIE Medical Imaging 2019.
• K. C. L Wong, M. Moradi, J. Wu, T. Syeda-Mahmood, “Identifying disease-free chest x-ray images with deep transfer learning”, SPIE Medical Imaging 2019: Computer-Aided Diagnosis.
• A Karargyris, S Kashyap, JT Wu, A Sharma, M. Moradi, T Syeda-Mahmood, “Age prediction using a large chest x-ray dataset”, SPIE Medical Imaging 2019: Computer-Aided Diagnosis.
• A. Harouni, H. Wang, T. Syeda-Mahmood, and D. Beymer. "Deep Network Anatomy Segmentation with Limited Annotations using Auxiliary Labels." In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 6-10. IEEE, 2019.
• A. Jadhav, J. Wu, T. Syeda-Mahmood. "Automatic extraction of structured radiology reports". Society for Imaging Informatics in Medicine (SIIM) 2019, Denver, Colorado, USA.
• A. Jadhav, J. Wu, T. Syeda-Mahmood. "Knowledge-driven approach to boost the performance of solely image-based deep learning models" Society for Imaging Informatics in Medicine (SIIM) 2019, Denver, Colorado, USA.
• A. Jadhav, T. Baldwin, J. Wu, V. Mukherjee, T. Syeda-Mahmood, "Automatic Patient Data Summarization for Radiologist", RSNA 2019.
• T. Syeda-Mahmood, J. Wu, M. Morris, B. Sabury, "Automatic structuring of radiology reports, “RSNA 2019.
• A. Pillai, A. Katouzian, A. Jadhav, M. Bendersky. K. Kanjaria, C. Shivade, V. Mukherjee, T. Syeda-Mahmood, “A knowledge-based question answering system to provide cognitive assistance to radiologists”, SPIE Medical Imaging 2019.
• V. Subramanian, H. Wang, Joy Wu, K. CL Wong, A. Sharma, T. Syeda-Mahmood, "Automated detection and type classification of central venous catheters in chest X-rays", MICCAI 2019.

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2018 publications

• T. Syeda-Mahmood, “Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology”, Journal of the American College of Radiology, 15(3), 569-576, 2018.
• A. Karargyris and T. Syeda-Mahmood, “Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation,” Proc. SPIE, vol.10575, February 2018.
• K. C. L. Wong, T. Syeda-Mahmood, M. Moradi, “Building medical image classifiers with very unbalanced and limited data using segmentation networks”, Medical Image Analysis 49, 105–116, 2018.
• H Wang, D Kakrania, H Tang, P Prasanna, T Syeda-Mahmood, “Fast Anatomy Segmentation by Combining Coarse Scale Multi-Atlas Label Fusion with Fine Scale Corrective Learning”, Computerized Medical Imaging and Graphics 68, 16-24, 2018.
• M. Moradi, A. Madani, Y. Guy, Y. Guo, T. Syeda-Mahmood, "Bimodal network architectures for automatic generation of image annotation from text", MICCAI 2018, pp. 449-456.
• Ken C. L. Wong, M. Moradi, H. Tang, T. Syeda-Mahmood, "3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes", MICCAI 2018, pp. 612-619.
• G. Veni, M. Moradi, H. Bulu, G. Narayan, T. Syeda-Mahmood, “Echocardiagraphy segmentation based on a shape-guided deformable model driven by a fully convolutional network prior”, IEEE ISBI 2018.
• A. Lu, E. Dehghan, M. Moradi, T. Syeda-Mahmood, “Detecting Anomalies from Echocardiography using Multi-View Regression of Clinical Measurements”, IEEE ISBI 2018.
• A. Madani, M. Moradi, A. Karargyris, T. Syeda-Mahmood, “Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation”, IEEE ISBI 2018.
• A. Harouni, A. Karargyris, M. Negahdar, D. Beymer, T. Syeda-Mahmood, "Universal multimodal deep network for classification and segmentation of medical images", IEEE ISBI 2018.
• H. Tang, M. Moradi, A. El harouni, H. Wang, P. Prasanna, G. Veni, T. Syeda-Mahmood, “Segmentation of anatomical structures in cardiac CTA using multi-label V-Net”, SPIE 2018.
• Ali Madani, M. Moradi, T. Syeda-Mahmood, A. Karargyris, “Chest x-ray generation and data augmentation for cardiovascular abnormality classification”, SPIE 2018.
• M.Negahdar, D. Beymer, T. Syeda-Mahmood, “Automated volumetric lung segmentation of thoracic CT images using fully convolutional neural network”, SPIE 2018.
• H. Tang, M. Moradi, C L Wong, H Wang, A El Harouni, T. Syeda-Mahmood, “Integrating deformable modeling with 3D deep neural network segmentation”, Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, pp. 377-384, 2018.
• T. Baldwin, Y. Guo, V. Mukherjee, T. Syeda-Mahmood, “Generalized Extraction and Classification of Span-Level Clinical Phrases,” in Proc. AMIA Annual Symposium, November 2018.
• Y. Guo, J. Wu, T. Baldwin, D. Beymer, V. Mukherjee, T. Syeda-Mahmood, “Improving the Path from Diagnoses to Documentation: A Cognitive Review Tool for Clinical Notes and Administrative Records,” in Proc. AMIA Annual Symposium, November 2018.
• M. Bendersky, Joy T. Wu, T. Syeda-Mahmood, “A comparative study of the classification of radiology reports,” BIBM, December 2018.

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2017 publications

• K. C. L. Wong, T. Syeda-Mahmood, M. Moradi, “Building medical image classifiers with very unbalanced and limited data using segmentation networks”, Medical Image Analysis, vol. 49, pp. 105–116, 2018.
• Y. Guo, D. Kakrania, T. Baldwin, T. Syeda-Mahmood, “Efficient Clinical Concept Extraction in Electronic Medical Records”. AAAI 2017: 5089-5090
• H. Wang, P. Prasanna, T. Syeda-Mahmood, “Fast anatomy segmentation by combining low resolution multi-atlas label fusion with high resolution corrective learning: An experimental study,” ISBI 2017: 223-226, 2017.
• H. Tang, M. Moradi, P. Prasanna, H. Wang, T. Syeda-Mahmood, “An algorithm for fully automatic detection of calcium in chest CT imaging,” ISBI 2017: 265-269, 2017.
• E. Dehghan, H. Wang, T. Syeda-Mahmood, “Automatic detection of aortic dissection in contrast-enhanced CT,” ISBI 2017: 557-560, 2017
• M. Moradi, Y. Guo, Y. Gur, T. Syeda-Mahmood, “Automatic labeling of continuous wave Doppler images based on combined image and sentence networks,” ISBI 2017: 667-670, 2017.
• M. Negahdar, M. Moradi, N. Parajuli, T. F. Syeda-Mahmood, “Automatic extraction of disease-specific features from Doppler images,” SPIE Medical Imaging: Computer-Aided Diagnosis 2017.
• H. Wang, M. Moradi, Y. Gur, P. Prasanna and T. F. Syeda-Mahmood, “A Multi-Atlas Approach to Region of Interest Detection for Medical Image Classification.” MICCAI 2017, pp. 168-176, 2017.
• K. Wong, M. Moradi, A. Karargyris, T. Syeda-Mahmood, Building Disease Detection Algorithms with Very Small Number of Positive Samples, in Proc. MICCAI 2017
• H. Wong, M. Moradi, Y. Gur, P. Prasanna, T. Syeda-Mahmood,” A multi-atlas approach to region of interest detection for medical image classification,” in Proc. MICCAI 2017

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2016 publications

• T. Baldwin, Y. Guo, T. Syeda-Mahmood, “Automatic Generation of Conditional Diagnostic Guidelines,” AMIA 2016.
• M. Moradi, Y. Gur, H. Wang, P. Prasanna, T. Syeda-Mahmood, “A hybrid learning approach for semantic labeling of cardiac CT slices and recognition of body position,” ISBI 2016: 1418-1421.
• T. F. Syeda-Mahmood, E. Walach, D. Beymer, F. Gilboa-Solomon, M. Moradi, P. Kisilev, D. Kakrania, C. B. Compas, H. Wang, M. Negahdar, Y. Cao, T. Baldwin, Y. Guo, Y. Gur, D. Rajan, A. Zlotnick, S. Rabinovici-Cohen, R. Ben-Ari, G. Amit, P. Prasanna, J. Morey, O. B. Boyko, S. Y. Hashoul, “Medical sieve: a cognitive assistant for radiologists and cardiologists,” SPIE Medical Imaging: Computer-Aided Diagnosis 2016.
• T. F. Syeda-Mahmood, Y. Guo, M. Moradi, D. Beymer, D. Rajan, Yu Cao, Y. Gur, M. Negahdar, “Identifying Patients at Risk for Aortic Stenosis Through Learning from Multimodal Data,” in Proc. MICCAI (3) 2016: 238-245
• M. Moradi, Y. Guo, Yaniv Gur, M. Negahdar, T. F. Syeda-Mahmood, “A Cross-Modality Neural Network Transform for Semi-automatic Medical Image Annotation,” MICCAI (2) 2016: 300-307, 2016.
• S. Conjeti, A Katouzian, A. Kazi, S. Mesbah, D. Beymer, T. F. Syeda-Mahmood, N. Navab, “Metric hashing forests” Medical Image Analysis 34: 13-29 (2016). Best Paper Award, MICCAI 2016.
• H. Zhang, P. Prasanna, J. Morey, T. Syeda-Mahmood, “Improving the Efficiency of Manual Ground Truth Labeling,” in Society of Imaging Informatics Conference, SIIM2016.
• D. Kakrania, T. Syeda-Mahmood, “A System for Rapidly Assembling Clinical Knowledge through Curation of Automatically Extracted Knowledge from Medical Knowledge Sources,” in Society of Imaging Informatics Conference, SIIM2016.

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