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Thomas A. Lasko
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2020 – today
- 2024
- [j25]Eric V. Strobl, Thomas A. Lasko
, Eric R. Gamazon
:
Mitigating pathogenesis for target discovery and disease subtyping. Comput. Biol. Medicine 171: 108122 (2024) - [j24]Thomas A. Lasko
, Eric V. Strobl, William W. Stead
:
Why do probabilistic clinical models fail to transport between sites. npj Digit. Medicine 7(1) (2024) - [i16]Thomas A. Lasko, John M. Still, Thomas Z. Li, Marco Barbero Mota, William W. Stead, Eric V. Strobl, Bennett A. Landman, Fabien Maldonado:
Unsupervised Discovery of Clinical Disease Signatures Using Probabilistic Independence. CoRR abs/2402.05802 (2024) - 2023
- [j23]Eric V. Strobl, Thomas A. Lasko:
Identifying patient-specific root causes with the heteroscedastic noise model. J. Comput. Sci. 72: 102099 (2023) - [j22]Xin Yu, Qi Yang
, Yinchi Zhou, Leon Y. Cai
, Riqiang Gao
, Ho Hin Lee
, Thomas Z. Li, Shunxing Bao
, Zhoubing Xu, Thomas A. Lasko, Richard G. Abramson, Zizhao Zhang, Yuankai Huo, Bennett A. Landman, Yucheng Tang:
UNesT: Local spatial representation learning with hierarchical transformer for efficient medical segmentation. Medical Image Anal. 90: 102939 (2023) - [c30]Eric V. Strobl, Thomas A. Lasko:
Generalizing Clinical Trials with Convex Hulls. CLeaR 2023: 197-221 - [c29]Eric V. Strobl, Thomas A. Lasko:
Sample-Specific Root Causal Inference with Latent Variables. CLeaR 2023: 895-915 - [c28]Thomas Z. Li, John M. Still, Kaiwen Xu, Ho Hin Lee, Leon Y. Cai, Aravind R. Krishnan, Riqiang Gao, Mirza S. Khan, Sanja Antic, Michael N. Kammer, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman, Thomas A. Lasko:
Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures from Routine EHRs for Pulmonary Nodule Classification. MICCAI (2) 2023: 649-659 - [c27]Thomas Z. Li, Kaiwen Xu, Riqiang Gao, Yucheng Tang, Thomas A. Lasko, Fabien Maldonado, Kim L. Sandler, Bennett A. Landman:
Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography. Medical Imaging: Image Processing 2023 - [i15]Thomas Z. Li, John M. Still, Kaiwen Xu, Ho Hin Lee, Leon Y. Cai, Aravind R. Krishnan, Riqiang Gao, Mirza S. Khan, Sanja Antic, Michael N. Kammer, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman, Thomas A. Lasko:
Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification. CoRR abs/2304.02836 (2023) - [i14]Thomas A. Lasko, Eric V. Strobl, William W. Stead:
Why Do Clinical Probabilistic Models Fail To Transport Between Sites? CoRR abs/2311.04787 (2023) - 2022
- [j21]Riqiang Gao
, Thomas Z. Li
, Yucheng Tang, Kaiwen Xu, Mirza S. Khan
, Michael N. Kammer, Sanja L. Antic, Stephen Deppen, Yuankai Huo, Thomas A. Lasko, Kim L. Sandler, Fabien Maldonado
, Bennett A. Landman:
Reducing uncertainty in cancer risk estimation for patients with indeterminate pulmonary nodules using an integrated deep learning model. Comput. Biol. Medicine 150: 106113 (2022) - [j20]Cailey I. Kerley
, Shikha Chaganti, Tin Q. Nguyen, Camilo Bermudez, Laurie E. Cutting, Lori L. Beason-Held, Thomas A. Lasko, Bennett A. Landman:
pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis. Neuroinformatics 20(2): 483-505 (2022) - [c26]Marco Barbero Mota, Jorge L. Gamboa, John M. Still, Charles M. Stein, Vivian K. Kawai, Thomas A. Lasko:
Validating Data-Driven Clinical Fingerprints as an Input Feature Representation. AMIA 2022 - [c25]Eric V. Strobl, Thomas A. Lasko:
Identifying patient-specific root causes of disease. BCB 2022: 18:1-18:10 - [i13]Xin Yu, Yucheng Tang, Yinchi Zhou, Riqiang Gao, Qi Yang, Ho Hin Lee, Thomas Z. Li, Shunxing Bao, Yuankai Huo, Zhoubing Xu, Thomas A. Lasko, Richard G. Abramson, Bennett A. Landman:
Characterizing Renal Structures with 3D Block Aggregate Transformers. CoRR abs/2203.02430 (2022) - [i12]Eric V. Strobl, Thomas A. Lasko:
Identifying Patient-Specific Root Causes of Disease. CoRR abs/2205.11627 (2022) - [i11]Eric V. Strobl, Thomas A. Lasko:
Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model. CoRR abs/2205.13085 (2022) - [i10]Riqiang Gao, Thomas Z. Li, Yucheng Tang, Zhoubing Xu, Michael N. Kammer, Sanja L. Antic, Kim L. Sandler, Fabien Maldonado, Thomas A. Lasko, Bennett A. Landman:
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging. CoRR abs/2206.08833 (2022) - [i9]Thomas Z. Li, Kaiwen Xu, Riqiang Gao, Yucheng Tang, Thomas A. Lasko, Fabien Maldonado, Kim L. Sandler, Bennett A. Landman:
Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography. CoRR abs/2209.01676 (2022) - [i8]Xin Yu, Qi Yang, Yinchi Zhou, Leon Y. Cai, Riqiang Gao, Ho Hin Lee, Thomas Z. Li, Shunxing Bao, Zhoubing Xu, Thomas A. Lasko, Richard G. Abramson, Zizhao Zhang, Yuankai Huo, Bennett A. Landman, Yucheng Tang:
UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation. CoRR abs/2209.14378 (2022) - [i7]Eric V. Strobl, Thomas A. Lasko:
Sample-Specific Root Causal Inference with Latent Variables. CoRR abs/2210.15340 (2022) - 2021
- [j19]Laurie Lovett Novak
, Jonathan P. Wanderer, David A. Owens, Daniel Fabbri, Julian Z. Genkins
, Thomas A. Lasko:
A Perioperative Care Display for Understanding High Acuity Patients. Appl. Clin. Inform. 12(01): 164-169 (2021) - [j18]Ziqi Zhang, Chao Yan
, Thomas A. Lasko
, Jimeng Sun
, Bradley A. Malin
:
SynTEG: a framework for temporal structured electronic health data simulation. J. Am. Medical Informatics Assoc. 28(3): 596-604 (2021) - [c24]Eric V. Strobl, Thomas A. Lasko:
Synthesized difference in differences. BCB 2021: 45:1-45:10 - [c23]Riqiang Gao, Yucheng Tang, Kaiwen Xu, Ho Hin Lee, Steve Deppen, Kim L. Sandler, Pierre P. Massion, Thomas A. Lasko, Yuankai Huo, Bennett A. Landman:
Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective. MICCAI (5) 2021: 647-656 - [i6]Eric V. Strobl, Thomas A. Lasko:
Synthesized Difference in Differences. CoRR abs/2105.00455 (2021) - [i5]Riqiang Gao, Yucheng Tang, Kaiwen Xu, Ho Hin Lee, Steve Deppen, Kim L. Sandler, Pierre P. Massion, Thomas A. Lasko, Yuankai Huo, Bennett A. Landman:
Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective. CoRR abs/2107.11882 (2021) - [i4]Eric V. Strobl, Thomas A. Lasko:
Generalizing Clinical Trials with Convex Hulls. CoRR abs/2111.13229 (2021) - 2020
- [j17]Thomas A. Lasko
, David A. Owens, Daniel Fabbri, Jonathan P. Wanderer, Julian Z. Genkins
, Laurie L. Novak
:
User-Centered Clinical Display Design Issues for Inpatient Providers. Appl. Clin. Inform. 11(05): 700-709 (2020) - [j16]Sharon E. Davis
, Robert A. Greevy Jr., Thomas A. Lasko, Colin G. Walsh
, Michael E. Matheny
:
Detection of calibration drift in clinical prediction models to inform model updating. J. Biomed. Informatics 112: 103611 (2020) - [c22]Sharon E. Davis, Robert A. Greevy Jr., Thomas A. Lasko, Colin G. Walsh, Michael E. Matheny:
A Surveillance Framework for Monitoring and Updating Clinical Prediction Models. AMIA 2020 - [c21]Colin B. Hansen, Vishwesh Nath, Riqiang Gao, Camilo Bermudez, Yuankai Huo, Kim L. Sandler, Pierre P. Massion, Jeffrey D. Blume, Thomas A. Lasko, Bennett A. Landman:
Semi-supervised Machine Learning with MixMatch and Equivalence Classes. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 112-121 - [i3]Colin B. Hansen, Vishwesh Nath, Diego A. Mesa, Yuankai Huo, Bennett A. Landman, Thomas A. Lasko:
The Value of Nullspace Tuning Using Partial Label Information. CoRR abs/2003.07921 (2020)
2010 – 2019
- 2019
- [j15]Qiang Wei
, Yukun Chen, Mandana Salimi, Joshua C. Denny
, Qiaozhu Mei, Thomas A. Lasko, Qingxia Chen, Stephen Wu, Amy Franklin
, Trevor Cohen, Hua Xu:
Cost-aware active learning for named entity recognition in clinical text. J. Am. Medical Informatics Assoc. 26(11): 1314-1322 (2019) - [j14]Sharon E. Davis
, Robert A. Greevy Jr., Christopher Fonnesbeck, Thomas A. Lasko, Colin G. Walsh, Michael E. Matheny
:
A nonparametric updating method to correct clinical prediction model drift. J. Am. Medical Informatics Assoc. 26(12): 1448-1457 (2019) - [j13]Shikha Chaganti
, Louise A. Mawn, Hakmook Kang
, Josephine Egan, Susan M. Resnick, Lori L. Beason-Held, Bennett A. Landman
, Thomas A. Lasko
:
Electronic Medical Record Context Signatures Improve Diagnostic Classification Using Medical Image Computing. IEEE J. Biomed. Health Informatics 23(5): 2052-2062 (2019) - [c20]Sharon E. Davis, Robert A. Greevy Jr., Thomas A. Lasko, Colin G. Walsh, Michael E. Matheny:
Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating. AMIA 2019 - [c19]Kimberley Kondratieff, Candace D. McNaughton, Michael E. Matheny, Thomas A. Lasko:
Longitudinal modeling of prescription refill records to predict medication use. AMIA 2019 - [c18]Shikha Chaganti, Camilo Bermudez, Louise A. Mawn, Thomas A. Lasko, Bennett A. Landman:
Contextual Deep Regression Network for Volume Estimation in Orbital CT. MICCAI (6) 2019: 104-111 - [i2]Yuankai Huo, James G. Terry, Jiachen Wang, Sangeeta Nair, Thomas A. Lasko, Barry I. Freedman, John Jeffrey Carr, Bennett A. Landman:
Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological Operations. CoRR abs/1906.09549 (2019) - 2018
- [j12]Sharidan K. Parr
, Matthew S. Shotwell, Alvin D. Jeffery
, Thomas A. Lasko, Michael E. Matheny
:
Automated mapping of laboratory tests to LOINC codes using noisy labels in a national electronic health record system database. J. Am. Medical Informatics Assoc. 25(10): 1292-1300 (2018) - [j11]Linda Zhang
, Daniel Fabbri, Thomas A. Lasko, Jesse M. Ehrenfeld, Jonathan P. Wanderer
:
A System for Automated Determination of Perioperative Patient Acuity. J. Medical Syst. 42(7): 123:1-123:11 (2018) - [c17]Joseph R. Coco, Cheng Ye, Chen Hajaj, Yevgeniy Vorobeychik, Joshua C. Denny, Laurie L. Novak, Bradley A. Malin, Thomas A. Lasko, Daniel Fabbri:
Crowdsourcing Clinical Chart Reviews. AMIA 2018 - [c16]Sharidan K. Parr, Thomas A. Lasko, Alvin D. Jeffery, Matthew S. Shotwell, Michael E. Matheny:
Automated Mapping of Laboratory Tests to LOINC Codes using Noisy Labels in a National Electronic Health Record System Database. AMIA 2018 - 2017
- [j10]Pedro L. Teixeira
, Wei-Qi Wei, Robert M. Cronin, Huan Mo
, Jacob P. VanHouten
, Robert J. Carroll, Eric LaRose, Lisa Bastarache, S. Trent Rosenbloom, Todd L. Edwards, Dan M. Roden, Thomas A. Lasko, Richard A. Dart, Anne M. Nikolai, Peggy L. Peissig, Joshua C. Denny
:
Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals. J. Am. Medical Informatics Assoc. 24(1): 162-171 (2017) - [j9]Sharon E. Davis
, Thomas A. Lasko, Guanhua Chen
, Edward D. Siew
, Michael E. Matheny
:
Calibration drift in regression and machine learning models for acute kidney injury. J. Am. Medical Informatics Assoc. 24(6): 1052-1061 (2017) - [j8]Yukun Chen, Thomas A. Lasko, Qiaozhu Mei, Qingxia Chen, Sungrim Moon, Jingqi Wang, Ky Nguyen, Tolulola Dawodu, Trevor Cohen
, Joshua C. Denny
, Hua Xu:
An active learning-enabled annotation system for clinical named entity recognition. BMC Medical Informatics Decis. Mak. 17(2): 35-44 (2017) - [c15]Sharon E. Davis, Thomas A. Lasko, Guanhua Chen, Michael E. Matheny:
Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality. AMIA 2017 - [c14]Jacek M. Bajor, Thomas A. Lasko:
Predicting Medications from Diagnostic Codes with Recurrent Neural Networks. ICLR (Poster) 2017 - [c13]Shikha Chaganti
, Jamie R. Robinson
, Camilo Bermudez
, Thomas A. Lasko, Louise A. Mawn
, Bennett A. Landman
:
EMR-Radiological Phenotypes in Diseases of the Optic Nerve and Their Association with Visual Function. DLMIA/ML-CDS@MICCAI 2017: 373-381 - 2016
- [c12]Jacob P. VanHouten, Christopher Fonnesbeck, Michael E. Matheny, Thomas A. Lasko:
The Discriminative Power of Non-Specific Laboratory Results. AMIA 2016 - [c11]Sharon E. Davis, Thomas A. Lasko, Guanhua Chen, Michael E. Matheny:
Calibration Drift of Clinical Prediction Models Across Modeling Methods. CRI 2016 - 2015
- [j7]Yukun Chen
, Thomas A. Lasko, Qiaozhu Mei, Joshua C. Denny
, Hua Xu:
A study of active learning methods for named entity recognition in clinical text. J. Biomed. Informatics 58: 11-18 (2015) - [c10]Thomas A. Lasko:
Nonstationary Gaussian Process Regression for Evaluating Repeated Clinical Laboratory Tests. AAAI 2015: 1777-1783 - [c9]Ravi V. Atreya, Thomas A. Lasko, Mia A. Levy:
Assessing Variability in Breast Cancer Treatment Paths Using Frequent Sequence Mining. AMIA 2015 - [c8]Yukun Chen, Sungrim Moon, Thomas A. Lasko, Qiaozhu Mei, Jingqi Wang, Trevor Cohen, Qingxia Chen, Joshua C. Denny, Hua Xu:
Real Time Active Learning Study for Clinical Named Entity Recognition. AMIA 2015 - 2014
- [j6]Jimeng Sun
, Candace D. McNaughton, Ping Zhang
, Adam Perer, Aris Gkoulalas-Divanis, Joshua C. Denny
, Jacqueline Kirby, Thomas A. Lasko, Alexander Saip, Bradley A. Malin
:
Predicting changes in hypertension control using electronic health records from a chronic disease management program. J. Am. Medical Informatics Assoc. 21(2): 337-344 (2014) - [c7]Jacob P. VanHouten, John Starmer, Nancy M. Lorenzi, David J. Maron, Thomas A. Lasko:
Machine Learning for Risk Prediction of Acute Coronary Syndrome. AMIA 2014 - [c6]Thomas A. Lasko:
Efficient Inference of Gaussian-Process-Modulated Renewal Processes with Application to Medical Event Data. UAI 2014: 469-476 - [i1]Thomas A. Lasko:
Efficient Inference of Gaussian Process Modulated Renewal Processes with Application to Medical Event Data. CoRR abs/1402.4732 (2014) - 2013
- [j5]Wei-Qi Wei, Robert M. Cronin, Hua Xu, Thomas A. Lasko, Lisa Bastarache, Joshua C. Denny
:
Development and evaluation of an ensemble resource linking medications to their indications. J. Am. Medical Informatics Assoc. 20(5): 954-961 (2013) - [c5]Ravi V. Atreya, Thomas A. Lasko, Mia A. Levy:
Role of ICD Granularity in Phenotyping Hematologic Malignancies for Tumor Registries. AMIA 2013 - [c4]Yukun Chen, Thomas A. Lasko, Qiaozhu Mei, Joshua C. Denny, Hua Xu:
A Study of Active Learning Methods for Clinical Entities Recognition. AMIA 2013 - [c3]Jacob P. VanHouten, John Starmer, Nancy M. Lorenzi, Thomas A. Lasko:
Random Forest Classification of Acute Coronary Syndromes. AMIA 2013 - 2012
- [j4]Robert J. Carroll, William K. Thompson, Anne E. Eyler, Arthur M. Mandelin, Tianxi Cai, Raquel M. Zink, Jennifer A. Pacheco
, Chad S. Boomershine, Thomas A. Lasko, Hua Xu, Elizabeth W. Karlson, Raúl G. Pérez, Vivian S. Gainer, Shawn N. Murphy, Eric M. Ruderman, Richard M. Pope
, Robert M. Plenge, Abel N. Kho, Katherine P. Liao, Joshua C. Denny
:
Portability of an algorithm to identify rheumatoid arthritis in electronic health records. J. Am. Medical Informatics Assoc. 19(e1) (2012) - 2010
- [j3]Thomas A. Lasko, Staal Amund Vinterbo:
Spectral Anonymization of Data. IEEE Trans. Knowl. Data Eng. 22(3): 437-446 (2010)
2000 – 2009
- 2007
- [b1]Thomas A. Lasko:
Spectral anonymization of data. Massachusetts Institute of Technology, Cambridge, MA, USA, 2007 - 2006
- [j2]Thomas A. Lasko, Steven J. Atlas, Michael J. Barry, Henry C. Chueh:
Research Paper: Automated Identification of a Physician's Primary Patients. J. Am. Medical Informatics Assoc. 13(1): 74-79 (2006) - 2005
- [j1]Thomas A. Lasko, Jui G. Bhagwat, Kelly H. Zou, Lucila Ohno-Machado
:
The use of receiver operating characteristic curves in biomedical informatics. J. Biomed. Informatics 38(5): 404-415 (2005) - 2002
- [c2]Thomas A. Lasko, Mitchell J. Feldman, G. Octo Barnett:
DXplain Evoking Strength - Clinician Interpretation and Consistency. AMIA 2002 - 2001
- [c1]Thomas A. Lasko, Susan E. Hauser:
Approximate string matching algorithms for limited-vocabulary OCR output correction. Document Recognition and Retrieval 2001: 232-240
Coauthor Index
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last updated on 2024-09-05 01:13 CEST by the dblp team
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