A Sarker, G Gonzalez-Hernandez, Y Ruan, J Perrone.
Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter.
JAMA Network Open, 2019; 2(11):e1914672. Nov 1. doi:10.1001/jamanetworkopen.2019.14672:
A Sarker, A DeRoos, J Perrone.
Mining social media for prescription medication abuse monitoring: a review and proposal for a data-centric framework
Journal of the American Medical Informatics Association. 2019. doi: 10.1093/jamia/ocz162:
Klein, Ari Z., Abeed Sarker, Davy Weissenbacher, and Graciela Gonzalez-Hernandez.
Towards scaling Twitter for digital epidemiology of birth defects
npj Digital Medicine. Volume 2, Article number: 96 (2019). doi: 10.1038/s41746-019-0170-5:
A Sarker, AZ Klein, J Mee, P Harik, G Gonzalez-Hernandez.
An interpretable natural language processing system for written medical examination assessment
Journal of Biomedical Informatics. Volume 98. October 2019, DOI: 10.1016/j.jbi.2019.103268. :
Davoudi, Anahita, Ari Z. Klein, Abeed Sarker, and Graciela Gonzalez-Hernandez.
Towards Automatic Bot Detection in Twitter for Health-related Tasks
arXiv preprint 2019; Accepted at AMIA Informatics Summit 2020:
Weissenbacher, Davy, Abeed Sarker, Ari Klein, Karen O'Connor, Arjun Magge Ranganatha, and Graciela Gonzalez-Hernandez.
Deep neural networks ensemble for detecting medication mentions in tweets
Journal of the American Medical Informatics Association, 26 (12), 1618-1626 2019 Dec 1 :
Weissenbacher, Davy, Abeed Sarker, Arjun Magge, Ashlynn Daughton, Karen O’Connor, Michael Paul, and Graciela Gonzalez..
Overview of the fourth Social Media Mining for Health (SMM4H) shared task at ACL 2019.
In: Proceedings of the 4th Social Media Mining for Health Applications (SMM4H) Workshop & Shared Task. 2019. August. Florence, Italy. Pages: 21-30. DOI: 10.18653/v1/W19-3203 :
Abeed Sarker, Graciela Gonzalez-Hernandez, and Jeanmarie Perrone.
Towards Automating Location-Specific Opioid Toxicosurveillance from Twitter via Data Science Methods
Stud Health Technol Inform; 264: 333-337, 2019 Aug 21. :
Mohammed Ali Al-garadi, Mohammad Rashid Hussain, Nawsher Khan, Ghulam Murtaza, Henry Friday Nweke, Ihsan Ali, Ghulam Mujtaba, Haruna Chiroma, Hasan Ali Khattak, Abdullah Gani.
Predicting Cyberbullying on Social Media in the Big Data Era Using Machine Learning Algorithms: Review of Literature and Open Challenges.
EEE Access, vol. 7, pp. 70701-70718, 2019. DOI: 10.1109/ACCESS.2019.2918354:
Magge, Arjun, Abeed Sarker, Azadeh Nikfarjam, and Graciela Gonzalez-Hernandez.
Comment on: Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.
Journal of the American Medical Informatics Association. 26 (6), 577-579. [Correspondence/Letter to the Editor]:
Nweke, Henry Friday, Ying Wah Teh, Ghulam Mujtaba, and Mohammed Ali Al-Garadi.
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions.
Information Fusion. Volume 46, March 2019, Pages 147-170.:
Klein, Ari Z., Abeed Sarker, Karen O’Connor, and Graciela Gonzalez-Hernande.
An Analysis of a Twitter Corpus for Training a Medication Intake Classifier.
AMIA Summits on Translational Science Proceedings. 2019. 102–106. PMID: 31258961:
Karen Smith, Su Golder, Abeed Sarker, Yoon Loke, Karen O’Connor, Graciela Gonzalez-Hernandez.
Methods to compare adverse events in Twitter to FAERS, drug information databases, and systematic reviews: proof of concept with adalimumab.
Drug safety 41, no. 12 (2018): 1397-1410.:
Abeed Sarker, Graciela Gonzalez-Hernandez.
An unsupervised and customizable misspelling generator for mining noisy health-related text sources.
Journal of biomedical informatics 88 (2018): 98-107.:
Ari Z Klein, Abeed Sarker, Haitao Cai, Davy Weissenbacher, Graciela Gonzalez-Hernandez.
Social media mining for birth defects research: a rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter.
Journal of biomedical informatics 87 (2018): 68-78.:
Graciela Gonzalez, Davy Weissenbacher, Abeed Sarker, Michael Paul.
Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task.
Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task.:
Davy Weissenbacher, Abeed Sarker, Michael Paul, Graciela Gonzalez.
Overview of the third social media mining for health (smm4h) shared tasks at emnlp 2018
In Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, pp. 13-16. 2018.:
Abeed Sarker, Maksim Belousov, Jasper Friedrichs, Kai Hakala, Svetlana Kiritchenko, Farrokh Mehryary, Sifei Han, Tung Tran, Anthony Rios, Ramakanth Kavuluru, Berry de Bruijn, Filip Ginter, Debanjan Mahata, Saif M Mohammad, Goran Nenadic, Graciela Gonzalez-Hernandez.
Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task Authors.
Journal of the American Medical Informatics Association 25, no. 10 (2018): 1274-1283.:
Nweke, Henry Friday, Ying Wah Teh, Mohammed Ali Al-Garadi, and Uzoma Rita Alo.
Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Expert Systems with Applications 105 (2018): 233-261.:
Masoud Rouhizadeh, Arjun Magge, Ari Klein, Abeed Sarker, Graciela Gonzalez.
A rule-based approach to determining pregnancy timeframe from contextual social media postings
In Proceedings of the 2018 International Conference on Digital Health, pp. 16-20. ACM, 2018.:
Abeed Sarker, Graciela Gonzalez.
HLP@ UPenn at SemEval-2017 Task 4A: A simple, self-optimizing text classification system combining dense and sparse vectors
In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pp. 640-643. 2017.:
Ari Klein, Abeed Sarker, Masoud Rouhizadeh, Karen O’Connor, Graciela Gonzalez.
Detecting personal medication intake in Twitter: an annotated corpus and baseline classification system
In BioNLP 2017, pp. 136-142. 2017.:
Abeed Sarker, Arjun Magge, Amit Sharma.
Dermatologic concerns communicated through Twitter
International journal of dermatology 56, no. 8 (2017): e162-e163.:
G Gonzalez-Hernandez, A Sarker, K O’Connor, G Savova.
Capturing the patient’s perspective: a review of advances in natural language processing of health-related text
Yearbook of medical informatics 26, no. 01 (2017): 214-227.:
Abeed Sarker, Diego Molla, Cecile Paris.
Automated text summarisation and evidence-based medicine: A survey of two domains
arXiv preprint arXiv:1706.08162 (2017).:
Mohammed Ali Al-garadi, Kasturi Dewi Varathan, Sri Devi Ravana.
Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method Authors
Physica A: Statistical Mechanics and its Applications 468 (2017): 278-288.:
Pramod Bharadwaj Chandrashekar, Arjun Magge, Abeed Sarker, Graciela Gonzalez.
Social media mining for identification and exploration of health-related information from pregnant women
arXiv preprint arXiv:1702.02261 (2017).:
Abeed Sarker, Graciela Gonzalez.
A corpus for mining drug-related knowledge from Twitter chatter: language models and their utilities
Data in brief 10 (2017): 122-131.:
Ehsan Emadzadeh, Abeed Sarker, Azadeh Nikfarjam, Graciela Gonzalez.
Hybrid semantic analysis for mapping adverse drug reaction mentions in tweets to medical terminology
In AMIA Annual Symposium Proceedings, vol. 2017, p. 679. American Medical Informatics Association, 2017.:
Davy Weissenbacher, Abeed Sarker, Tasnia Tahsin, Matthew Scotch, Graciela Gonzalez.
Extracting geographic locations from the literature for virus phylogeography using supervised and distant supervision methods
AMIA Summits on Translational Science Proceedings 2017 (2017): 114.:
Abeed Sarker, Pramod Chandrashekar, Arjun Magge, Haitao Cai, Ari Klein, Graciela Gonzalez.
Discovering cohorts of pregnant women from social media for safety surveillance and analysis
Journal of medical Internet research 19, no. 10 (2017): e361.:
Graciela Gonzalez-Hernandez, Abeed Sarker, Karen O’Connor, Casey Greene, Hongfang Liu.
Advances in text mining and visualization for precision medicine
In Proceedings of the Pacific Symposium on Biocomputing, pp. 590-601. 2017.:
Abeed Sarker, Graciela Gonzalez.
Data, tools and resources for mining social media drug chatter
Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016), pp. 99-107. 2016.:
Diego Mollá, María Elena Santiago-Martínez, Abeed Sarker, Cécile Paris.
A corpus for research in text processing for evidence based medicine
Language Resources and Evaluation 50, no. 4 (2016): 705-727.:
Abbas Chokor, Abeed Sarker, Graciela Gonzalez.
Mining the web for pharmacovigilance: the case study of duloxetine and venlafaxine
arXiv preprint arXiv:1610.02567 (2016):
Ioannis Korkontzelos, Azadeh Nikfarjam, Matthew Shardlow, Abeed Sarker, Sophia Ananiadou, Graciela H Gonzalez.
Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts
Journal of biomedical informatics 62 (2016): 148-158.:
Al-garadi, Mohammed Ali, Muhammad Sadiq Khan, Kasturi Dewi Varathan, Ghulam Mujtaba, and Abdelkodose M. Al-Kabsi.
Using online social networks to track a pandemic: A systematic review
Journal of biomedical informatics 62 (2016): 1-11.:
Abeed Sarker, Graciela Gonzalez.
DIEGOLab16 at SemEval-2016 Task 4: Sentiment analysis in Twitter using centroids, clusters, and sentiment lexicons
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp. 209-214. 2016.:
Al-garadi, Mohammed Ali, Kasturi Dewi Varathan, and Sri Devi Ravana.
Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network
Computers in Human Behavior 63 (2016): 433-443:
Abeed Sarker, K O’Connor, R Ginn, M Scotch, K Smith, Dan Malone, G Gonzalez.
Social media mining for toxicovigilance: automatic monitoring of prescription medication abuse from Twitter
Drug Safety. Pages 1-10. DOI: 10.1007/s40264-015-0379-4. 2016:
Abeed Sarker, Graciela Gonzalez.
Social media mining for toxicovigilance: automatic monitoring of prescription medication abuse from Twitter
Drug safety 39, no. 3 (2016): 231-240.:
Abeed Sarker, Azadeh Nikfarjam, Graciela Gonzalez.
Social media mining shared task workshop
In Biocomputing 2016: Proceedings of the Pacific Symposium, pp. 581-592. 2016.:
Michael J Paul, Abeed Sarker, John S Brownstein, Azadeh Nikfarjam, Matthew Scotch, Karen L Smith, Graciela Gonzalez.
Social media mining for public health monitoring and surveillance
In Biocomputing 2016: Proceedings of the Pacific symposium, pp. 468-479. 2016:
Abeed Sarker, Diego Mollá, Cecile Paris.
Query oriented evidence extraction to support evidence-based medicine practice
Journal of biomedical informatics 59 (2016): 169-184.:
Abeed Sarker, Azadeh Nikfarjam, Davy Weissenbacher, Graciela Gonzalez.
Diegolab: An approach for message-level sentiment classification in twitter
In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pp. 510-514. 2015.:
Abeed Sarker, Diego Mollá, Cécile Paris.
Automatic evidence quality prediction to support evidence-based decision making
Artificial intelligence in medicine, 64(2), 89-103:
Abeed Sarker, R Ginn, A Nikfarjam, K O’Connor, K Smith, S Jayaraman, T Upadhaya, G Gonzalez.
Utilizing social media data for pharmacovigilance: a review
Journal of Biomedical Informatics (JBI). Volume 54. Pages 202-212. DOI: http://dx.doi.org/10.1016/j.jbi.2015.02.004. 2015. [Editor’s choice; Nominated for ATLAS (September, 2015):
Nikfarjam, Azadeh, Abeed Sarker, Karen O’Connor, Rachel Ginn, and Graciela Gonzalez.
Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
Journal of the American Medical Informatics Association 22, no. 3 (2015): 671-681.:
Abeed Sarker, Graciela Gonzalez.
Portable automatic text classification for adverse drug reaction detection via multi-corpus training
Journal of Biomedical Informatics (JBI). Volume 53. Pages: 196-207. DOI: 10.1016/j.jbi.2014.11.002. 2014:
Ginn, Rachel, Pranoti Pimpalkhute, Azadeh Nikfarjam, Apurv Patki, Karen O’Connor, Abeed Sarker, Karen Smith, and Graciela Gonzalez.
Mining Twitter for adverse drug reaction mentions: a corpus and classification benchmark.
In Proceedings of the fourth workshop on building and evaluating resources for health and biomedical text processing, pp. 1-8. 2014.:
K O’Connor, A Nikfarjam, R Ginn, P Pimpalkhute, A Sarker, K Smith, G Gonzalez.
Pharmacovigilance on twitter? Mining tweets for adverse drug reactions.
In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA). 2014: