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Indika Kahanda
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Journal Articles
- 2022
- [j6]Sandali Lokuge, Shyaman Jayasundara, Puwasuru Ihalagedara, Indika Kahanda, Damayanthi Herath:
miRNAFinder: A comprehensive web resource for plant Pre-microRNA classification. Biosyst. 215-216: 104662 (2022) - 2021
- [j5]Morteza Pourreza Shahri, Indika Kahanda:
Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes. BMC Bioinform. 22(1): 500 (2021) - 2019
- [j4]Buwani Manuweera, Gillian Reynolds, Indika Kahanda:
Computational methods for the ab initio identification of novel microRNA in plants: a systematic review. PeerJ Comput. Sci. 5: e233 (2019) - [j3]Alan M. Cleary, Thiruvarangan Ramaraj, Indika Kahanda, Joann Mudge, Brendan Mumey:
Exploring Frequented Regions in Pan-Genomic Graphs. IEEE ACM Trans. Comput. Biol. Bioinform. 16(5): 1424-1435 (2019) - 2018
- [j2]Julien Gobeill, Pascale Gaudet, Daniel Dopp, Adam Morrone, Indika Kahanda, Yi-Yu Hsu, Chih-Hsuan Wei, Zhiyong Lu, Patrick Ruch:
Overview of the BioCreative VI text-mining services for Kinome Curation Track. Database J. Biol. Databases Curation 2018: bay104 (2018) - 2015
- [j1]Christopher S. Funk, Indika Kahanda, Asa Ben-Hur, Karin M. Verspoor:
Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct. J. Biomed. Semant. 6: 9 (2015)
Conference and Workshop Papers
- 2024
- [c29]Guna Sekaran Jaganathan, Nazmul Kazi, Indika Kahanda, Upulee Kanewala:
Poster: Towards Understanding Root Causes of Real Failures in Healthcare Machine Learning Applications. ICST 2024: 430-433 - [c28]Guna Sekaran Jaganathan, Nazmul Kazi, Indika Kahanda, Upulee Kanewala:
MLHCBugs: A Framework to Reproduce Real Faults in Healthcare Machine Learning Applications. ICST 2024: 445-447 - 2023
- [c27]Conrad T. Testagrose, Vikash Gupta, Barbaros S. Erdal, Richard D. White, Robert W. Maxwell, Xudong Liu, Indika Kahanda, Sherif Elfayoumy, William Klostermeyer, Mutlu Demirer:
Breast-Density Semantic Segmentation with Probability Scaling for BI-RADS Assessment using DeepLabV3. BCB 2023: 25:1-25:6 - [c26]Indika Kahanda, Buwani Manuweera, Brendan Mumey, Thiruvarangan Ramaraj, Alan M. Cleary, Joann Mudge:
Genotype-to-Phenotype Associations with Frequented Region Variants. BIBM 2023: 114-119 - [c25]Prajwol Lamichhane, Indika Kahanda, Xudong Liu, Karthikeyan Umapathy, Sandeep Reddivari, Catherine Christie, Andrea Arikawa, Jenifer Ross:
Poster: BioFactCheck: Exploring the Feasibility of Explainable Automated Inconsistency Detection in Biomedical and Health Literature. CHASE 2023: 196-197 - [c24]Nazmul Kazi, Indika Kahanda, S. Indu Rupassara, John W. Kindt:
Zero-Shot Information Extraction with Community-Fine-Tuned Large Language Models From Open-Ended Interview Transcripts. ICMLA 2023: 932-937 - [c23]Conrad Testagrose, Athlene V. Jones, Indika Kahanda:
Patronizing and Condescending Language Detection. ICMLA 2023: 1132-1137 - [c22]Guna Sekaran Jaganathan, Grentina Kilungeja, Indika Kahanda:
UNF-IDT: Automated Irony Detection in English Tweets. ICMLA 2023: 1514-1519 - [c21]Nazmul Kazi, Indika Kahanda:
Enhancing Transfer Learning of LLMs through Fine- Tuning on Task - Related Corpora for Automated Short-Answer Grading. ICMLA 2023: 1687-1691 - [c20]Prajwol Lamichhane, Indika Kahanda:
Enhancing Health Information Retrieval with Large Language Models: A Study on MedQuAD Dataset. ICMLA 2023: 2147-2152 - 2022
- [c19]Conrad Testagrose, Vikash Gupta, Barbaros S. Erdal, Richard D. White, Robert W. Maxwell, Xudong Liu, Indika Kahanda, Sherif Elfayoumy, William Klostermeyer, Mutlu Demirer:
Impact of Concatenation of Digital Craniocaudal Mammography Images on a Deep-Learning Breast-Density Classifier Using Inception-V3 and ViT. BIBM 2022: 3399-3406 - 2021
- [c18]Morteza Pourreza Shahri, Katrina Lyon, Julia Schearer, Indika Kahanda:
DeepPPPred: Deep Ensemble Learning with Transformers, Recurrent and Convolutional Neural Networks for Human Protein-Phenotype Co-mention Classification. BIBM 2021: 2869-2876 - [c17]Francis Anokye, Indika Kahanda:
BioSGAN: Protein-Phenotype Co-mention Classification Using Semi-Supervised Generative Adversarial Networks. CBMS 2021: 468-473 - [c16]Nazmul Kazi, Nathaniel Lane, Indika Kahanda:
Automatically Cataloging Scholarly Articles using Library of Congress Subject Headings. EACL (Student Research Workshop) 2021: 43-49 - [c15]Lucas Welch, Xudong Liu, Indika Kahanda, Sandeep Reddivari, Karthikeyan Umapathy:
Vegetation Coverage in Marsh Grass Photography Using Convolutional Neural Networks. FLAIRS 2021 - 2020
- [c14]Puwasuru Ihalagedara, Sandali Lokuge, Shyaman Jayasundara, Damayanthi Herath, Indika Kahanda:
miRNAFinder: A pre-microRNA classifier for plants and analysis of feature impact. CIBCB 2020: 1-7 - [c13]Karishma Rahman, Indika Kahanda, Upulee Kanewala:
MRpredT: Using Text Mining for Metamorphic Relation Prediction. ICSE (Workshops) 2020: 420-424 - [c12]Nathaniel Lane, Indika Kahanda:
DeepACPpred: A Novel Hybrid CNN-RNN Architecture for Predicting Anti-Cancer Peptides. PACBB 2020: 60-69 - [c11]Daniel Laden, Shyaman Jayasundara, Indika Kahanda:
RDoCer: Information Retrieval and Sentence Extraction for Mental Health using Research Domain Criteria. ICSC 2020: 226-229 - [c10]Morteza Pourreza Shahri, Indika Kahanda:
ProPheno 1.0: An Online Dataset for Accelerating the Complete Characterization of the Human Protein-Phenotype Landscape in Biomedical Literature. ICSC 2020: 416-423 - 2019
- [c9]Morteza Pourreza Shahri, Madhusudan Srinivasan, Gillian Reynolds, Diane Bimczok, Indika Kahanda, Upulee Kanewala:
Metamorphic Testing for Quality Assurance of Protein Function Prediction Tools. AITest 2019: 140-148 - [c8]Morteza Pourreza Shahri, Gillian Reynolds, Mandi Marie Roe, Indika Kahanda:
PPPred: Classifying Protein-phenotype Co-mentions Extracted from Biomedical Literature. BCB 2019: 414-422 - [c7]Buwani Manuweera, Joann Mudge, Indika Kahanda, Brendan Mumey, Thiruvarangan Ramaraj, Alan M. Cleary:
Poster: Pangenome-Wide Association Studies with Frequented Regions. BCB 2019: 537 - [c6]Buwani Manuweera, Joann Mudge, Indika Kahanda, Brendan Mumey, Thiruvarangan Ramaraj, Alan M. Cleary:
Pangenome-Wide Association Studies with Frequented Regions. BCB 2019: 627-632 - [c5]Mohammad Anani, Nazmul Kazi, Matthew Kuntz, Indika Kahanda:
RDoC Task at BioNLP-OST 2019. BioNLP-OST@EMNLP-IJNCLP 2019: 216-226 - 2018
- [c4]Madhusudan Srinivasan, Morteza Pourreza Shahri, Indika Kahanda, Upulee Kanewala:
Quality Assurance of Bioinformatics Software: A Case Study of Testing a Biomedical Text Processing Tool Using Metamorphic Testing. MET@ICSE 2018: 26-33 - 2017
- [c3]Indika Kahanda, Asa Ben-Hur:
GOstruct 2.0: Automated Protein Function Prediction for Annotated Proteins. BCB 2017: 60-66 - [c2]Alan M. Cleary, Indika Kahanda, Brendan Mumey, Joann Mudge, Thiruvarangan Ramaraj:
Exploring Frequented Regions in Pan-Genomic Graphs. BCB 2017: 89-97 - 2009
- [c1]Indika Kahanda, Jennifer Neville:
Using Transactional Information to Predict Link Strength in Online Social Networks. ICWSM 2009
Informal and Other Publications
- 2019
- [i5]Morteza Pourreza Shahri, Madhusudan Srinivasan, Gillian Reynolds, Diane Bimczok, Indika Kahanda, Upulee Kanewala:
Metamorphic Testing for Quality Assurance of Protein Function Prediction Tools. CoRR abs/1904.08007 (2019) - [i4]Morteza Pourreza Shahri, Indika Kahanda:
ProPheno: An online dataset for completely characterizing the human protein-phenotype landscape in biomedical literature. PeerJ Prepr. 7: e27479 (2019) - [i3]Nazmul Kazi, Indika Kahanda:
Automatically generating psychiatric case notes from digital transcripts of doctor-patient conversations using text mining. PeerJ Prepr. 7: e27497 (2019) - 2018
- [i2]Madhusudan Srinivasan, Morteza Pourreza Shahri, Upulee Kanewala, Indika Kahanda:
Quality Assurance of Bioinformatics Software: A Case Study of Testing a Biomedical Text Processing Tool Using Metamorphic Testing. CoRR abs/1802.07354 (2018) - [i1]Morteza Pourreza Shahri, Madhusudan Srinivasan, Diane Bimczok, Upulee Kanewala, Indika Kahanda:
A look back at the quality of Protein Function Prediction tools in CAFA. PeerJ Prepr. 6: e27161 (2018)
Coauthor Index
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