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ORCIDAaron J. Masino
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2020 – today
- 2023
[j11]Sarah M. Kark, Michelle A. Worthington, Richard H. Christie, Aaron J. Masino:
Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management. Frontiers Digit. Health 5 (2023)- [j10]Jacob R. Epifano
, Ravi Prakash Ramachandran, Aaron J. Masino, Ghulam Rasool:
Revisiting the fragility of influence functions. Neural Networks 162: 581-588 (2023) - [i5]Jacob R. Epifano, Ravi Prakash Ramachandran, Aaron J. Masino, Ghulam Rasool:
Revisiting the Fragility of Influence Functions. CoRR abs/2303.12922 (2023) - [i4]Jacob R. Epifano, Stephen Glass, Ravi Prakash Ramachandran, Sharad Patel, Aaron J. Masino, Ghulam Rasool:
Deployment of a Robust and Explainable Mortality Prediction Model: The COVID-19 Pandemic and Beyond. CoRR abs/2311.17133 (2023) - 2022
- [i3]Carla Floricel, Jacob R. Epifano, Stephanie Caamano, Sarah M. Kark, Rich Christie, Aaron J. Masino, Andre D. Paredes:
Opening Access to Visual Exploration of Audiovisual Digital Biomarkers: an OpenDBM Analytics Tool. CoRR abs/2210.01618 (2022) - 2021
- [j9]Xueqin Pang, Christopher B. Forrest, Félice Lê-Scherban, Aaron J. Masino:
Prediction of early childhood obesity with machine learning and electronic health record data. Int. J. Medical Informatics 150: 104454 (2021) - [c13]Elizabeth A. Campbell, Saurav Bose, Aaron J. Masino:
Obesity Classifier Performance Disparities by Demographic Subgroup. AMIA 2021 - [c12]Aaron J. Masino, Mary Catherine Harris, Lakshmi Srinivasan, Robert W. Grundmeier:
Longitudinal Performance of a Machine Learning NICU Sepsis Predictor. AMIA 2021 - 2020
- [j8]Elizabeth A. Campbell, Ellen J. Bass, Aaron J. Masino:
Temporal condition pattern mining in large, sparse electronic health record data: A case study in characterizing pediatric asthma. J. Am. Medical Informatics Assoc. 27(4): 558-566 (2020)
2010 – 2019
- 2019
- [j7]Anne Cocos, Alexander G. Fiks, Aaron J. Masino:
Reply to comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts". J. Am. Medical Informatics Assoc. 26(6): 580-581 (2019) - [c11]Aaron J. Masino, Daniel Forsyth, Heather Nuske, John Herrington, Jeffrey W. Pennington, Yelena Kushleyeva, Christopher P. Bonafide:
m-Health and Autism: Recognizing Stress and Anxiety with Machine Learning and Wearables Data. CBMS 2019: 714-719 - [c10]Xueqin Pang, Christopher B. Forrest, Félice Lê-Scherban, Aaron J. Masino:
Understanding Early Childhood Obesity via Interpretation of Machine Learning Model Predictions. ICMLA 2019: 1438-1443 - 2018
- [j6]Aaron J. Masino, Daniel Forsyth, Alexander G. Fiks:
Detecting Adverse Drug Reactions on Twitter with Convolutional Neural Networks and Word Embedding Features. J. Heal. Informatics Res. 2(1-2): 25-43 (2018) - [c9]Aaron J. Masino, Mary Catherine Harris, Daniel Forsyth, Svetlana Ostapenko, Robert W. Grundmeier:
Machine Learning Models for Infant Sepsis Prediction. AMIA 2018 - [c8]Mengnan Zhao, Aaron J. Masino, Christopher C. Yang:
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity. BioNLP 2018: 156-160 - [i2]Aaron J. Masino, Kaitlin A. Folweiler:
Unsupervised learning with GLRM feature selection reveals novel traumatic brain injury phenotypes. CoRR abs/1812.00030 (2018) - 2017
- [j5]Anne Cocos, Alexander G. Fiks, Aaron J. Masino:
Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts. J. Am. Medical Informatics Assoc. 24(4): 813-821 (2017) - [j4]Anne Cocos, Ting Qian, Chris Callison-Burch, Aaron J. Masino:
Crowd control: Effectively utilizing unscreened crowd workers for biomedical data annotation. J. Biomed. Informatics 69: 86-92 (2017) - [i1]Anne Cocos, Aaron J. Masino:
Combining rule-based and neural network systems for extracting adverse reactions from drug labels. TAC 2017 - 2016
- [j3]Aaron J. Masino, T. Charles Casper, Jonathan Michael Dean, Jamie Bell, Rene Enriquez, Sara J. Deakyne Davies, James Chamberlain, Elizabeth R. Alpern, Robert Grundmeier:
Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement. Appl. Clin. Inform. 07(04): 1051-1068 (2016) - [j2]Aaron J. Masino, Robert Grundmeier, Jeffrey W. Pennington, John A. Germiller, E. Bryan Crenshaw:
Temporal bone radiology report classification using open source machine learning and natural langue processing libraries. BMC Medical Informatics Decis. Mak. 16: 65 (2016) - [c7]Anne Cocos, Ting Qian, Aaron J. Masino:
Effectively Crowdsourcing Radiology Report Annotations. CRI 2016 - [c6]Daniel Forsyth, Anne Cocos, Aaron J. Masino:
Radiology Report Text Classification with Automatically Generated Regular Expression Pattern Features. CRI 2016 - [c5]Aaron J. Masino, Daniel Forsyth, Alexander G. Fiks:
Twitter Data Collection for ADHD Adverse Drug Event Detection. CRI 2016 - [c4]Ting Qian, Aaron J. Masino:
Identifying Subsets of "Big Data" Relevant for Hearing Loss Progression Research. CRI 2016 - 2015
- [c3]Anne Cocos, Aaron J. Masino, Ting Qian, Ellie Pavlick, Chris Callison-Burch:
Effectively Crowdsourcing Radiology Report Annotations. Louhi@EMNLP 2015: 109-114 - [c2]Aaron J. Masino, Robert Grundmeier, Jeffrey W. Pennington, E. Bryan Crenshaw:
Identifying Abnormal Anatomy on Temporal Bone Computed Tomography Reports Using Readily Available Natural Language Processing Software. AMIA 2015 - [c1]Alex S. Felmeister, Tyler J. Rivera, Aaron J. Masino, Adam C. Resnick, Jeffrey W. Pennington:
Scalable biobanking: A modular electronic Honest Broker and Biorepository for integrated clinical, specimen and genomic research. BIBM 2015: 484-490 - 2014
- [j1]Aaron J. Masino, Elizabeth T. Dechene, Matthew C. Dulik, Alisha Wilkens, Nancy B. Spinner, Ian D. Krantz, Jeffrey W. Pennington, Peter N. Robinson, Peter S. White:
Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology. BMC Bioinform. 15: 248 (2014)
Coauthor Index
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