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Jitendra Jonnagaddala
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2020 – today
- 2024
- [c21]Shagoofa Rakhshanda, Siaw-Teng Liaw, Joel Rhee, Kerry-Anne Rye, Jitendra Jonnagaddala:
Strategies to Address Statin Medication Intolerance Among Patients at Risk of Cardiovascular Disease Identified Through Electronic Health Records: A Literature Review and Pooled Analysis. MIE 2024: 132-136 - [c20]Mifetika Lukitasari, Jitendra Jonnagaddala, Siaw-Teng Liaw, Bin Jalaludin:
Approaches for Evaluating Visit-to-Visit Blood Pressure Variability as a Cardiovascular Disease Risk Factor: A Scoping Review. MIE 2024: 349-353 - [c19]Jiaxing Liu, Zoie Shui-Yee Wong, Jitendra Jonnagaddala:
Preliminary Evaluation of Fine-Tuning the OpenDeLD Deidentification Pipeline Across Multi-Center Corpora. MIE 2024: 719-723 - [c18]Mifetika Lukitasari, Jitendra Jonnagaddala, Siaw-Teng Liaw, Bin Jalaludin:
Association Between Visit to Visit Blood Pressure Variability and Cardiovascular Outcome: A Meta-Analysis. Nursing Informatics 2024: 262-266 - 2023
- [j20]David Susic, Shabbir Syed-Abdul, Erik Dovgan, Jitendra Jonnagaddala, Anton Gradisek:
Artificial intelligence based personalized predictive survival among colorectal cancer patients. Comput. Methods Programs Biomed. 231: 107435 (2023) - [c17]Shagoofa Rakhshanda, Siaw-Teng Liaw, Joel Rhee, Kerry-Anne Rye, Jitendra Jonnagaddala:
Strategies to Improve Statin Medication Adherence Among Patients at Risk of Cardiovascular Disease Identified Through Electronic Health Records: A Literature Review. MedInfo 2023: 986-990 - [c16]Mifetika Lukitasari, Siaw-Teng Liaw, Bin Jalaludin, Jitendra Jonnagaddala:
Visit-to-Visit Blood Pressure Variability in Cardiovascular Disease. MedInfo 2023: 1358-1359 - [i6]Min Cen, Xingyu Li, Bangwei Guo, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu:
Time to Embrace Natural Language Processing (NLP)-based Digital Pathology: Benchmarking NLP- and Convolutional Neural Network-based Deep Learning Pipelines. CoRR abs/2302.10406 (2023) - [i5]Min Cen, Xingyu Li, Bangwei Guo, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu:
DPSeq: A Novel and Efficient Digital Pathology Classifier for Predicting Cancer Biomarkers using Sequencer Architecture. CoRR abs/2305.01968 (2023) - 2022
- [j19]Xingyu Li, Jitendra Jonnagaddala, Min Cen, Hong Zhang, Xu Steven:
Colorectal Cancer Survival Prediction Using Deep Distribution Based Multiple-Instance Learning. Entropy 24(11): 1669 (2022) - [i4]Xingyu Li, Jitendra Jonnagaddala, Min Cen, Hong Zhang, Xu Steven Xu:
Colorectal cancer survival prediction using deep distribution based multiple-instance learning. CoRR abs/2204.11294 (2022) - [i3]Bangwei Guo, Jitendra Jonnagaddala, Hong Zhang, Xu Steven Xu:
Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: Achieving SOTA with Less Data using Swin Transformer. CoRR abs/2208.10495 (2022) - 2021
- [j18]Jitendra Jonnagaddala, Myron Anthony Godinho, Siaw-Teng Liaw:
From telehealth to virtual primary care in Australia? A Rapid scoping review. Int. J. Medical Informatics 151: 104470 (2021) - [j17]Diana Barsasella, Srishti Gupta, Shwetambara Malwade, Aminin, Yanti Susanti, Budi Tirmadi, Agus Mutamakin, Jitendra Jonnagaddala, Shabbir Syed-Abdul:
Predicting length of stay and mortality among hospitalized patients with type 2 diabetes mellitus and hypertension. Int. J. Medical Informatics 154: 104569 (2021) - [j16]Siaw-Teng Liaw, Jason Guan Nan Guo, Sameera Ansari, Jitendra Jonnagaddala, Myron Anthony Godinho, Alder Jose Borelli, Simon de Lusignan, Daniel Capurro, Harshana Liyanage, Navreet Bhattal, Vicki Bennett, Jaclyn Chan, Michael G. Kahn:
Quality assessment of real-world data repositories across the data life cycle: A literature review. J. Am. Medical Informatics Assoc. 28(7): 1591-1599 (2021) - [j15]Solveig K. Sieberts, Jennifer Schaff, Marlena Duda, Bálint Á Pataki, Ming Sun, Phil Snyder, Jean-Francois Daneault, Federico Parisi, Gianluca Costante, Udi Rubin, Peter Banda, Yooree Chae, Elias Chaibub Neto, Earl Ray Dorsey, Zafer Aydin, Aipeng Chen, Laura L. Elo, Carlos Espino, Enrico Glaab, Ethan Goan, Fatemeh Noushin Golabchi, Yasin Görmez, Maria K. Jaakkola, Jitendra Jonnagaddala, Riku Klén, Dongmei Li, Christian McDaniel, Dimitri Perrin, Thanneer M. Perumal, Nastaran Mohammadian Rad, Erin Rainaldi, Stefano Sapienza, Patrick Schwab, Nikolai Shokhirev, Mikko S. Venäläinen, Gloria Vergara-Diaz, Yuqian Zhang, Avner G. S. Abrami, Aditya Adhikary, Carla Agurto, Sherry Bhalla, Halil Ibrahim Bilgin, Vittorio Caggiano, Jun Cheng, Eden Deng, Qiwei Gan, Rajan Girsa, Zhi Han, Stephen Heisig, Kun Huang, Samad Jahandideh, Wolfgang Kopp, Christoph F. Kurz, Gregor Lichtner, Raquel Norel, G. P. S. Raghava, Tavpritesh Sethi, Nicholas Shawen, Vaibhav Tripathi, Matthew Tsai, Tongxin Wang, Yi Wu, Jie Zhang, Xinyu Zhang, Yuanjia Wang, Yuanfang Guan, Daniela Brunner, Paolo Bonato, Lara M. Mangravite, Larsson Omberg:
Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge. npj Digit. Medicine 4 (2021) - [i2]Xingyu Li, Jitendra Jonnagaddala, Shuhua Yang, Hong Zhang, Xu Steven Xu:
A Retrospective Analysis using Deep-Learning Models for Prediction of Survival Outcome and Benefit of Adjuvant Chemotherapy in Stage II/III Colorectal Cancer. CoRR abs/2111.03532 (2021) - 2020
- [j14]Myron Anthony Godinho, Jitendra Jonnagaddala, Nachiket Gudi, Rubana Islam, Padmanesan Narasimhan, Siaw-Teng Liaw:
mHealth for Integrated People-Centred Health Services in the Western Pacific: A Systematic Review. Int. J. Medical Informatics 142: 104259 (2020) - [j13]Hong-Jie Dai, Feng-Duo Wang, Chih-Wei Chen, Chu-Hsien Su, Chi-Shin Wu, Jitendra Jonnagaddala:
Cohort selection for clinical trials using multiple instance learning. J. Biomed. Informatics 107: 103438 (2020) - [j12]Jiawen Yao, Xinliang Zhu, Jitendra Jonnagaddala, Nicholas J. Hawkins, Junzhou Huang:
Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks. Medical Image Anal. 65: 101789 (2020) - [c15]Anna Ostropolets, Christian G. Reich, Patrick B. Ryan, Chunhua Weng, Anthony Molinaro, Frank J. DeFalco, Jitendra Jonnagaddala, Siaw-Teng Liaw, Hokyun Jeon, Rae Woong Park, Matthew E. Spotnitz, Karthik Natarajan, Kristin Kostka, George Argyriou, Robert T. Miller, Andrew E. Williams, Evan Minty, José D. Posada, George Hripcsak:
Characterizing database granularity using SNOMED-CT hierarchy. AMIA 2020 - [c14]Ashwin Raju, Jiawen Yao, Mohammad MinHazul Haq, Jitendra Jonnagaddala, Junzhou Huang:
Graph Attention Multi-instance Learning for Accurate Colorectal Cancer Staging. MICCAI (5) 2020: 529-539 - [i1]Jiawen Yao, Xinliang Zhu, Jitendra Jonnagaddala, Nicholas J. Hawkins, Junzhou Huang:
Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Learning Networks. CoRR abs/2009.11169 (2020)
2010 – 2019
- 2019
- [j11]Hong-Jie Dai, Chen-Kai Wang, Nai-Wen Chang, Ming-Siang Huang, Jitendra Jonnagaddala, Feng-Duo Wang, Wen-Lian Hsu:
Statistical principle-based approach for recognizing and normalizing microRNAs described in scientific literature. Database J. Biol. Databases Curation 2019: baz030 (2019) - [j10]Guan Nan Guo, Jitendra Jonnagaddala, Sanjay Farshid, Vojtech Huser, Christian G. Reich, Siaw-Teng Liaw:
Comparison of the cohort selection performance of Australian Medicines Terminology to Anatomical Therapeutic Chemical mappings. J. Am. Medical Informatics Assoc. 26(11): 1237-1246 (2019) - [j9]Kha Vo, Jitendra Jonnagaddala, Siaw-Teng Liaw:
Statistical supervised meta-ensemble algorithm for medical record linkage. J. Biomed. Informatics 95 (2019) - [c13]Aipeng Chen, Jitendra Jonnagaddala, Chandini Nekkantti, Siaw-Teng Liaw:
Generation of Surrogates for De-Identification of Electronic Health Records. MedInfo 2019: 70-73 - [r1]Onkar Singh, Nai-Wen Chang, Hong-Jie Dai, Jitendra Jonnagaddala:
Translational Bioinformatics Databases. Encyclopedia of Bioinformatics and Computational Biology (2) 2019: 1058-1062 - 2018
- [j8]Andon Tchechmedjiev, Amine Abdaoui, Vincent Emonet, Soumia Melzi, Jitendra Jonnagaddala, Clément Jonquet:
Enhanced functionalities for annotating and indexing clinical text with the NCBO Annotator+. Bioinform. 34(11): 1962-1965 (2018) - [c12]Harshana Liyanage, Siaw-Teng Liaw, Jitendra Jonnagaddala, William Hinton, Simon de Lusignan:
Common Data Models (CDMs) to Enhance International Big Data Analytics: A Diabetes Use Case to Compare Three CDMs. EFMI-STC 2018: 60-64 - 2017
- [c11]Jitendra Jonnagaddala, Feiyan Hu:
Automatic Coding of Death Certificates to ICD-10 Terminology. CLEF (Working Notes) 2017 - [c10]Yi-Jie Huang, Chu-Hsien Su, Yi-Chun Chang, Tseng-Hsin Ting, Tzu-Yuan Fu, Rou-Min Wang, Hong-Jie Dai, Yung-Chun Chang, Jitendra Jonnagaddala, Wen-Lian Hsu:
Incorporating Dependency Trees Improve Identification of Pregnant Women on Social Media Platforms. DDDSM@IJCNLP 2017: 26-32 - [c9]Dillon C. Adam, Jitendra Jonnagaddala, Daniel Han-Chen, Sean Batongbacal, Luan Almeida, Jing Z. Zhu, Jenny J. Yang, Jumail M. Mundekkat, Steven Badman, Abrar Chughtai, C. Raina MacIntyre:
ZikaHack 2016: A digital disease detection competition. DDDSM@IJCNLP 2017: 39-46 - [e1]Jitendra Jonnagaddala, Hong-Jie Dai, Yung-Chun Chang:
Proceedings of the International Workshop on Digital Disease Detection using Social Media, DDDSM@IJCNLP 2017, Taipei, Taiwan, November 27, 2017. Association for Computational Linguistics 2017, ISBN 978-1-948087-07-0 [contents] - 2016
- [j7]Hong-Jie Dai, Onkar Singh, Jitendra Jonnagaddala, Emily Chia-Yu Su:
NTTMUNSW BioC modules for recognizing and normalizing species and gene/protein mentions. Database J. Biol. Databases Curation 2016 (2016) - [j6]Hong-Jie Dai, Chu-Hsien Su, Po-Ting Lai, Ming-Siang Huang, Jitendra Jonnagaddala, Toni Rose Jue, Shruti Rao, Hui-Jou Chou, Marija Milacic, Onkar Singh, Syed Abdul Shabbir, Wen-Lian Hsu:
MET network in PubMed: a text-mined network visualization and curation system. Database J. Biol. Databases Curation 2016 (2016) - [j5]Jitendra Jonnagaddala, Toni Rose Jue, Nai-Wen Chang, Hong-Jie Dai:
Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion. Database J. Biol. Databases Curation 2016 (2016) - [j4]Sun Kim, Rezarta Islamaj Dogan, Andrew Chatr-aryamontri, Christie S. Chang, Rose Oughtred, Jennifer M. Rust, Riza Batista-Navarro, Jacob Carter, Sophia Ananiadou, Sérgio Matos, André Santos, David Campos, José Luís Oliveira, Onkar Singh, Jitendra Jonnagaddala, Hong-Jie Dai, Emily Chia-Yu Su, Yung-Chun Chang, Yu-Chen Su, Chun-Han Chu, Chien Chin Chen, Wen-Lian Hsu, Yifan Peng, Cecilia N. Arighi, Cathy H. Wu, K. Vijay-Shanker, Ferhat Aydin, Zehra Melce Hüsünbeyi, Arzucan Özgür, Soo-Yong Shin, Dongseop Kwon, Kara Dolinski, Mike Tyers, W. John Wilbur, Donald C. Comeau:
BioCreative V BioC track overview: collaborative biocurator assistant task for BioGRID. Database J. Biol. Databases Curation 2016 (2016) - [j3]Hong-Jie Dai, Musa Touray, Jitendra Jonnagaddala, Syed Abdul Shabbir:
Feature Engineering for Recognizing Adverse Drug Reactions from Twitter Posts. Inf. 7(2): 27 (2016) - [c8]Chen-Kai Wang, Hong-Jie Dai, Chih-Wei Chen, Jitendra Jonnagaddala, Nai-Wen Chang:
Combining Multiple Classifiers Using Global Ranking for ReachOut.com Post Triage. CLPsych@HLT-NAACL 2016: 176-179 - [c7]Jitendra Jonnagaddala, Joanne L. Croucher, Toni Rose Jue, Nicola S. Meagher, Lena Caruso, Robyn Ward, Nicholas J. Hawkins:
Integration and Analysis of Heterogeneous Colorectal Cancer Data for Translational Research. Nursing Informatics 2016: 387-391 - 2015
- [j2]Nai-Wen Chang, Hong-Jie Dai, Jitendra Jonnagaddala, Chih-Wei Chen, Richard Tzong-Han Tsai, Wen-Lian Hsu:
A context-aware approach for progression tracking of medical concepts in electronic medical records. J. Biomed. Informatics 58: S150-S157 (2015) - [j1]Jitendra Jonnagaddala, Siaw-Teng Liaw, Pradeep Ray, Manish Kumar, Nai-Wen Chang, Hong-Jie Dai:
Coronary artery disease risk assessment from unstructured electronic health records using text mining. J. Biomed. Informatics 58: S203-S210 (2015) - [c6]Jitendra Jonnagaddala, Hong-Jie Dai, Pradeep Ray, Siaw-Teng Liaw:
A preliminary study on automatic identification of patient smoking status in unstructured electronic health records. BioNLP@IJCNLP 2015: 147-151 - [c5]Jitendra Jonnagaddala, Siaw-Teng Liaw, Pradeep Ray:
Impact of data quality assessment on development of clinical predictive models. MedInfo 2015: 1069 - [c4]Jitendra Jonnagaddala, Siaw-Teng Liaw, Pradeep Kumar Ray, Manish Kumar, Hong-Jie Dai:
TMUNSW: Identification of Disorders and Normalization to SNOMED-CT Terminology in Unstructured Clinical Notes. SemEval@NAACL-HLT 2015: 394-398 - [c3]Josan Wei-San Lin, Hong-Jie Dai, Jitendra Jonnagaddala, Nai-Wun Chang, Toni Rose Jue, Usman Iqbal, Joni Yu-Hsuan Shao, I-Jen Chiang, Yu-Chuan Li:
Utilizing different word representation methods for twitter data in adverse drug reactions extraction. TAAI 2015: 260-265 - 2014
- [c2]Jitendra Jonnagaddala, Manish Kumar, Hong-Jie Dai, Enny Rachmani, Chien-Yeh Hsu:
TMUNSW: Disorder Concept Recognition and Normalization in Clinical Notes for SemEval-2014 Task 7. SemEval@COLING 2014: 663-667 - [c1]Jitendra Jonnagaddala, Siaw-Teng Liaw, Pradeep Ray, Manish Kumar, Hong-Jie Dai:
HTNSystem: Hypertension Information Extraction System for Unstructured Clinical Notes. TAAI 2014: 219-227
Coauthor Index
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last updated on 2024-10-23 20:30 CEST by the dblp team
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