Publications

selected publications

recent publications (2017 ~)

2024

• Abul Hasan, Jinge Wu, Quang Ngoc Nguyen, Salomé Andres, Imane Guellil, Huayu Zhang, Arlene Casey, Beatrice Alex, Bruce Guthrie, Honghan Wu. “Infusing clinical knowledge into tokenisers for language models.” arXiv preprint arXiv:2406.14312 (2024). arXiv:2406.14312

• Wu, Zhaolong, Abul Hasan, Jinge Wu, Yunsoo Kim, Jason PY Cheung, Teng Zhang, and Honghan Wu. “Chain-of-Though (CoT) prompting strategies for medical error detection and correction.” arXiv e-prints (2024): arXiv-2406. Accepted by NAACL 2024 Workshop Clinical NLP. arXiv:2406.09103

• Wu, Jinge, Abul Hasan, and Honghan Wu. “RadBARTsum: Domain Specific Adaption of Denoising Sequence-to-Sequence Models for Abstractive Radiology Report Summarization.” arXiv preprint arXiv:2406.03062 (2024). arXiv:2406.03062

• Shaoxiong Ji, Xiaobo Li, Wei Sun, Hang Dong, Ara Taalas, Yijia Zhang, Honghan Wu, Esa Pitkänen, Pekka Marttinen. “A Unified Review of Deep Learning for Automated Medical Coding.” ACM Computing Surveys. Accepted in May 2024. doi:10.1145/3664615 (2024).

• Wu, Jinge, Hang Dong, Zexi Li, Arijit Patra, Honghan Wu. “Retrieving and Refining: A Hybrid Framework with Large Language Models for Rare Disease Identification.” arXiv preprint 2405.10440 (2024). arXiv:2405.10440

• Kim, Yunsoo, Jinge Wu, Yusuf Abdulle, Yue Gao, and Honghan Wu. “Enhancing Human-Computer Interaction in Chest X-ray Analysis using Vision and Language Model with Eye Gaze Patterns.” arXiv preprint arXiv:2404.02370 (2024). Accepted by MICCAI 2024. arXiv:2404.02370

• Greene, Charlotte, Luke Blackbourn, Stuart McGurnaghan, Stewart Mercer, Daniel Smith, Sarah Wild, Honghan Wu, and Caroline Jackson. “Antidepressant and antipsychotic prescribing in patients with type 2 diabetes in Scotland: a time-trend analysis from 2004-2021.” Preprint from Authorea Preprints, (2024). DOI:10.22541/au.171195299.97836905/v1

• Francis, Farah, Saturnino Luz, Honghan Wu, Sarah J. Stock, and Rosemary Townsend. “Machine learning on cardiotocography data to classify fetal outcomes: A scoping review.” Computers in Biology and Medicine (2024): 108220. DOI:10.1016/j.compbiomed.2024.108220

• Hama, Tuankasfee, Mohanad Alsaleh, Freya Allery, Jung Won Choi, Chris Tomlinson, Honghan Wu, Alvina Lai, Nikolas Pontikos, and Johan H. Thygesen. “Enhancing Patient Outcome Prediction through Deep Learning with Sequential Diagnosis Codes from structural EHR: A systematic review.” Researchgate

• Wu, Jinge, Yunsoo Kim, and Honghan Wu. “Hallucination Benchmark in Medical Visual Question Answering.” arXiv preprint arXiv:2401.05827 (2024). arXiv:2401.05827

2023

• Emily Groves, Minhong Wang, Yusuf Abdulle, Holger Kunz, Jason Hoelscher-Obermaier, Ronin Wu, and Honghan Wu. “Benchmarking and Analyzing In-context Learning, Fine-tuning and Supervised Learning for Biomedical Knowledge Curation: a focused study on chemical entities of biological interest.” arXiv preprint arXiv:2312.12989 (2023). arXiv:2312.12989

• Jinge Wu, Yunsoo Kim, Eva C. Keller, Jamie Chow, Adam P. Levine, Nikolas Pontikos, Zina Ibrahim, Paul Taylor, Michelle C. Williams, and Honghan Wu. “Exploring Multimodal Large Language Models for Radiology Report Error-checking.” arXiv preprint arXiv:2312.13103 (2023). arXiv:2312.13103

• Wei Feng, Honghan Wu, Hui Ma, Zhenhuan Tao, Mengdie Xu, Xin Zhang, Shan Lu, Cheng Wan, and Yun Liu. “Applying contrastive pre-training for depression and anxiety risk prediction in type 2 diabetes patients based on heterogeneous electronic health records: a primary healthcare case study.” Journal of the American Medical Informatics Association (2023): ocad228. DOI:10.1093/jamia/ocad228

• Tudor Groza, Honghan Wu, Marcel E Dinger, Daniel Danis, Coleman Hilton, Anita Bagley, Jon R Davids, Ling Luo, Zhiyong Lu, Peter N Robinson. “Term-BLAST-Like Alignment Tool for Concept Recognition in Noisy Clinical Texts.” Bioinformatics (2023): btad716. DOI:10.1093/bioinformatics/btad716

• Zhang, Huayu, Arlene Casey, Imane Guellil, Víctor Suárez-Paniagua, Clare Macrae, Charis Marwick, Honghan Wu, Bruce Guthrie, and Beatrice Alex. “FLAP: A framework for linking free-text addresses to the Ordnance Survey Unique Property Reference Number database.” Frontiers in Digital Health 5: 1186208. DOI: 10.3389/fdgth.2023.1186208

• Casey, Arlene, Emma Davidson, Claire Grover, Richard Tobin, Andreas Grivas, Huayu Zhang, Patrick Schrempf, Alison Q. O’Neil, Liam Lee, Michael Walsh, Freya Pellie, Karen Ferguson, Vera Cvoro, Honghan Wu, Heather Whalley, Grant Mair, William Whiteley, Beatrice Alex. “Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports.” Frontiers in Digital Health 5 (2023): 1184919. DOI: 10.3389/fdgth.2023.1184919

• Fu, Yinghua, Ge Zhang, Xin Lu, Honghan Wu, and Dawei Zhang. “RMCA U-net: Hard exudates segmentation for retinal fundus images.” Expert Systems with Applications 234 (2023): 120987. DOI:10.1016/j.eswa.2023.120987

• Jinge Wu, Daqian Shi, Abul Hasan, and Honghan Wu. 2023. “KnowLab at RadSum23: comparing pre-trained language models in radiology report summarization.” In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 535–540, Toronto, Canada. Association for Computational Linguistics. DOI:10.18653/v1/2023.bionlp-1.54

• Hang Dong, Víctor Suárez-Paniagua, Huayu Zhang, Minhong Wang, Arlene Casey, Emma Davidson, Jiaoyan Chen, Beatrice Alex, William Whiteley & Honghan Wu. “Ontology-driven and weakly supervised rare disease identification from clinical notes”. BMC Medical Informatics and Decision Making (2023). DOI:10.1186/s12911-023-02181-9 .

• Mohanad M. Alsaleh, Freya Allery, Jung Won Choi, Tuankasfee Hama, Andrew McQuillin, Honghan Wu, Johan H. Thygesen. ‘Prediction of disease comorbidity using explainable artificial intelligence and machine learning techniques: A systematic review’. International Journal of Medical Informatics (2023).DOI:10.1016/j.ijmedinf.2023.105088 .

• Charlotte R.L. Greene, Hanna Ward-Penny, Marianna F. Ioannou, Sarah H. Wild, Honghan Wu, Daniel J. Smith, Caroline A. Jackson. “Antidepressant and antipsychotic drug prescribing and diabetes outcomes: A systematic review of observational studies”. Diabetes Research and Clinical Practice (2023). DOI:10.1016/j.diabres.2023.110649 .

• Wu, Jinge, Rowena Smith, and Honghan Wu. “Ontology-Driven Self-Supervision for Adverse Childhood Experiences Identification Using Social Media Datasets.” In Proceedings of the 1st Workshop on Scarce Data in Artificial Intelligence for Healthcare - SDAIH, ISBN 978-989-758-629-3, SciTePress, pages 5-10. DOI: 10.5220/0011531100003523, pdf, Github Repo

• Aneeta Sylolypavan, Derek Sleeman, Honghan Wu, and Malcolm Sim. “The impact of inconsistent human annotations on AI driven clinical decision making.” npj Digital Medicine 6, 26 (2023). DOI:10.1038/s41746-023-00773-3 .

2022

• Honghan Wu, Minhong Wang, Jinge Wu, Farah Francis, Yun-Hsuan Chang, Alex Shavick, Hang Dong, et al. “A Survey on Clinical Natural Language Processing in the United Kingdom from 2007 to 2022”. npj Digital Medicine 5, 186 (2022). DOI:10.1038/s41746-022-00730-6 .

• Hang Dong, Matúš Falis, William Whiteley, Beatrice Alex, Joshua Matterson, Shaoxiong Ji, JiaoyanChen & Honghan Wu. “Automated Clinical Coding - What, Why, and Where We Are.” npj Digital Medicine 5, 159 (2022). DOI:10.1038/s41746-022-00705-7 .

• Aneeta Sylolypavan, Derek Sleeman, Honghan Wu, and Malcolm Sim. The Impact of Inconsistent Human Annotations on AI driven Clinical Decision Making. Preprint: doi:10.21203/rs.3.rs-1937575/v1, Oct 2022.

• Minhong Wang, Farah Francis, Holger Kunz, Xiang Zhang, Cheng Wan, Yun Liu, Paul Taylor, Sarah H.Wild, Honghan Wu. “Artificial intelligence models for predicting cardiovascular diseases in people with type 2 diabetes: a systematic review.” Accepted by Intelligence-Based Medicine. DOI:10.1016/j.ibmed.2022.100072, Aug 2022.

• Cheng Wan, Steph Read, Honghan Wu, Shan Lu, Xin Zhang, Sarah H. Wild, and Yun Liu. Prediction of Five-Year Cardiovascular Disease Risk in People with Type 2 Diabetes Mellitus: Derivation in Nanjing, China and External Validation in Scotland, UK. Global Heart. 2022;17(1):46. DOI: 10.5334/gh.1131.

• Xihe Kuang, Jason Pui Yin Cheung, Kwan-Yee K. Wong, Wai Yi Lam, Chak Hei Lam, Richard W. Choy, Christopher P. Cheng, Honghan Wu, Cao Yang, Kun Wang, Yang Li, Teng Zhang. Spine-GFlow: A Hybrid Learning Framework for Robust Multi-tissue Segmentation in Lumbar MRI without Manual Annotation, Computerized Medical Imaging and Graphics, 2022, 102091, ISSN 0895-6111, DOI:10.1016/j.compmedimag.2022.102091.

• Johan H Thygesen, Christopher Tomlinson, Sam Hollings, Mehrdad Mizani, Alex Handy, Ashley Akbari Orcid Logo, Amitava Banerjee, Jennifer Cooper, Alvina Lai, Ken Li, Bilal Mateen, Naveed Sattar, Reecha Sofat, Ana Torralbo, Honghan Wu, Angela Wood, Jonathan A C Sterne, Christina Pagel, William Whiteley, Cathie Sudlow, Harry Hemingway, Spiros Denaxas. “COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records”. Lancet Digital Health. June 2022. DOI:10.1016/S2589-7500(22)00091-7 .

• Honghan Wu, Minhong Wang, Aneeta Sylolypavan, Sarah Wild. “Quantifying Health Inequalities Induced by Data and AI Models”. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22), Special Track on AI for Good. Vienna 23-29 July, 2022. IJCAI-Proceedings, preprint, slides, recording, repo.

• Isabel Straw and Honghan Wu. “Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction”. BMJ Health & Care Informatics 2022;29:e100457. doi: 10.1136/bmjhci-2021-100457 (April 2022).

• Qingyu Chen, Alexis Allot, Robert Leaman, Rezarta Islamaj Doğan, Jingcheng Du, Li Fang, Kai Wang, Shuo Xu, Yuefu Zhang, Parsa Bagherzadeh, Sabine Bergler, Aakash Bhatnagar, Nidhir Bhavsar, Yung-Chun Chang, Sheng-Jie Lin, Wentai Tang, Hongtong Zhang, Ilija Tavchioski, Senja Pollak, Shubo Tian, Jinfeng Zhang, Yulia Otmakhova, Antonio Jimeno Yepes, Hang Dong, Honghan Wu, Richard Dufour, Yanis Labrak, Niladri Chatterjee, Kushagri Tandon, Fréjus Laleye, Loïc Rakotoson, Emmanuele Chersoni, Jinghang Gu, Annemarie Friedrich, Subhash Chandra Pujari, Mariia Chizhikova, Naveen Sivadasan, Naveen Sivadasan, Zhiyong Lu. Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations, Database, Volume 2022, 2022, baac069, DOI:10.1093/database/baac069 arXiv:2204.09781.

• Huayu Zhang, Johan H. Thygesen, Ting Shi, Georgios Gkoutos, Harry Hemingway , Bruce Guthrie, Honghan Wu and Genomics England Research Consortium “Increased COVID-19 mortality rate in rare disease patients: a retrospective cohort study in participants of the Genomics England 100,000 Genomes project”. Orphanet Journal of Rare Diseases 17, 166 (2022). April 2022. DOI:10.1186/s13023-022-02312-x. preprint version.

• Ji, Shaoxiong, Wei Sun, Hang Dong, Honghan Wu, and Pekka Marttinen. “A Unified Review of Deep Learning for Automated Medical Coding.” arXiv preprint arXiv:2201.02797 (2022).

2021

• L. Mirza, J. Das-Munshi, J. Chaturvedi, H. Wu, Z. Kraljewic, T. Searle, S. Shaari, A. Mascio, N. Skiada, A. Roberts, D. Bean, R. Stewart, R. Dobson, and R. Bendayan, “Investigating the Association between Physical Health Comorbidities and Disability in Individuals with Severe Mental Illness,” European Psychiatry, pp. 1–33, 2021. DOI: 10.1192/j.eurpsy.2021.2255

• Huayu Zhang, Johan Thygesen, Honghan Wu. Increased COVID-19 related mortality rate for patients with rare diseases: a retrospective cohort study with data from Genomics England. The Lancet, Volume 398, S95. November 2021. (Conference Abstract) DOI: 10.1016/S0140-6736(21)02638-6

• Davidson, Emma M., Michael TC Poon, Arlene Casey, Andreas Grivas, Daniel Duma, Hang Dong, Víctor Suárez-Paniagua, Claire Grover, Richard Tobin, Heather Whalley, Honghan Wu, Beatrice Alex & William Whiteley. “The reporting quality of natural language processing studies: systematic review of studies of radiology reports.” BMC Medical Imaging 21, no. 1 (2021): 1-13. DOI:10.1186/s12880-021-00671-8

• Dong H, Suárez-Paniagua V, Zhang H, Wang M, Whitfield E, Wu H. Rare Disease Identification from Clinical Notes with Ontologies and Weak Supervision. Accepted for 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2021), 2021 Nov 01-05. p. 1-5. arXiv:2105.01995

• Ibrahim, Zina M., Daniel Bean, Thomas Searle, Honghan Wu, Anthony Shek, Zeljko Kraljevic, James Galloway, Sam Norton, James T. Teo, and Richard JB Dobson. “A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data.” In press: IEEE Journal of Biomedical and Health Informatics. DOI: 10.1109/JBHI.2021.3089287 (2021).

• Kristiina Rannikmäe, Honghan Wu, Steven Tominey, William Whiteley, Naomi Allen and Cathie Sudlow. Developing automated methods for disease subtyping in UK Biobank: an exemplar study on stroke. BMC Medical Informatics and Decision Making. Volume 21, Article number: 191 (2021). DOI:10.1186/s12911-021-01556-0.

• Casey A, Davidson E, Poon M, Dong H, Duma D, Grivas A, Grover C, Suárez-Paniagua V, Tobin R, Whiteley W, Wu H, Alex B. A Systematic Review of Natural Language Processing Applied to Radiology Reports. BMC Medical Informatics and Decision Making. Volume 21, , Article number: 179 (2021). DOI:10.1186/s12911-021-01533-7.

• Hang Dong, Víctor Suárez-Paniagua, Huayu Zhang, Minhong Wang, Emma Whitfield and Honghan Wu. Weakly supervised entity linking and ontology matching to enrich patients’ rare disease coding. Poster. Accepted to Workshop on Personal Health Knowledge Graphs 2021.

• Emma Whitfield, Claire Coffey, Huayu Zhang, Ting Shi, Xiaodong Wu, Qiang Li, Honghan Wu. Axes of Prognosis: Identifying Subtypes of COVID-19 Outcomes. AMIA 2021 Annual Symposium Proc 2021:1198-1207. October 2021, San Diego, USA. PMID: 35308999; PMCID: PMC8861682; medRxiv. DOI:10.1101/2021.03.16.21253371. Github Repo

• Hang Dong, Víctor Suárez-Paniagua, William Whiteley, Honghan Wu. Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation. Journal of Biomedical Informatics. 116 (2021): 103728. February 2021. DOI:10.1016/j.jbi.2021.103728, GitHub Repo

• Huayu Zhang, Amy Ferguson, Grant Robertson, Muchen Jiang, Teng Zhang, Cathie Sudlow, Keith Smith, Kristiina Rannikmae, Honghan Wu. Benchmarking network-based gene prioritization methods for cerebral small vessel disease. Briefings in Bioinformatics. February 2021. DOI:10.1093/bib/bbab006. GitHub Repo

2020

• Honghan Wu, Huayu Zhang, Andreas Karwath, Zina Ibrahim, Ting Shi, Xin Zhang, Kun Wang, Jiaxing Sun, Kevin Dhaliwal, Daniel Bean, Victor Roth Cardoso, Kezhi Li, James T. Teo, Amitava Banerjee, Fang Gao-Smith, Tony Whitehouse, Tonny Veenith, Georgios V. Gkoutos, Xiaodong Wu, Richard Dobson, and Bruce Guthrie. Ensemble learning for poor prognosis predictions: a case study on SARS-CoV2. November 2020. Accepted by Journal of the American Medical Informatics Association: DOI:10.1093/jamia/ocaa295. GitHub Repo

• Ewan Carr, Rebecca Bendayan, Daniel Bean, Matthew Stammers, Wenjuan Wang, Huayu Zhang, Thomas Searle, Zeljko Kraljevic, Anthony Shek, Hang T T Phan, Walter Muruet, Anthony J Shinton, Ting Shi, Xin Zhang, Andrew Pickles, Daniel Stahl, Rosita Zakeri, Kevin O’Gallagher, Amos Folarin, Lukasz Roguski, Florina Borca, James Batchelor, Xiaodong Wu, Jiaxing Sun, Ashwin Pinto, Bruce Guthrie, Cormac Breen, Abdel Douiri, Honghan Wu, Vasa Curcin, James T Teo, Ajay Shah, Richard Dobson. Evaluation and Improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study. BMC Med 19, 23 (2021). https://doi.org/10.1186/s12916-020-01893-3

• Amitava Banerjee, Suliang Chen, Laura Pasea, Alvina Lai, Michail Katsoulis, Spiros Denaxas, Vahe Nafilyan, Bryan Williams, Wai Keong Wong, Ameet Bakhai, Kamlesh Khunti, Deenan Pillay, Mahdad Noursadeghi, Honghan Wu, Nilesh Pareek, Daniel Bromage, Theresa Mcdonagh, Jonathan Byrne, James T Teo, Ajay Shah, Ben Humberstone, Liang V Tang, Anoop SV Shah, Andrea Rubboli, Yutao Guo, Yu Hu, Cathie LM Sudlow, Gregory YH Lip, Harry Hemingway. Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic. 2021. European Journal of Preventive Cardiology, zwaa155, https://doi.org/10.1093/eurjpc/zwaa155.

• Huayu Zhang, Ting Shi, Xiaodong Wu, Xin Zhang, Kun Wang, Daniel Bean, Richard Dobson, James T Teo, Jiaxing Sun, Pei Zhao, Chenghong Li, Kevin Dhaliwal, Honghan Wu, Qiang Li, Bruce Guthrie. Risk prediction for poor outcome and death in hospital in-patients with COVID-19: derivation in Wuhan, China and external validation in London, UK. 2020. Preprint: MedRxiv.

• Rebecca Bendayan, Honghan Wu, Zeljko Kraljevic, Robert Stewart, Tom Searle, Jaya Chaturvedi, Jayati Das-Munshi, Zina Ibrahim, Aurelie Mascio, Angus Roberts, Daniel Bean and Richard Dobson. Identifying physical health comorbidities in a cohort of individuals with severe mental illness: An application of SemEHR. Accepted by HealTAC 2020, London.

• Zina Ibrahim, Honghan Wu and Ricahrd Dobson. Modeling Rare Interactions in Time Series Data Through Qualitative Change: Application to Outcome Prediction in Intensive Care Units. Accepted by ECAI 2020, Santiago, Spain.

• Zina M Ibrahim, Honghan Wu, Ahmed Hamoud, Lukas Stappen, Richard J B Dobson, Andrea Agarossi, On classifying sepsis heterogeneity in the ICU: insight using machine learning, Journal of the American Medical Informatics Association, 2020, ocz211, https://doi.org/10.1093/jamia/ocz211

2019

• Honghan Wu, Minhong Wang, Qianyi Zeng, Wenjun Chen, Jeff Z. Pan, Cathie Sudlow, Dave Robertson. Knowledge Driven Phenotyping. Preprint: medrxiv doi:10.1101/19013748

• Pirathiv Kugathasan, HonghanWu, Fiona Gaughrancd, René Ernst Nielsen, Megan Pritchard, Richard Dobson, Robert Stewart, Brendon Stubbs. Association of physical health multimorbidity with mortality in people with schizophrenia spectrum disorders: Using a novel semantic search system that captures physical diseases in electronic patient records. Accepted/In press: Schizophrenia Research. 2019. DOI:10.1016/j.schres.2019.10.061

• Daniel M. Bean, James Teo, Honghan Wu, Ricardo Oliveira, Raj Patel, Rebecca Bendayan, Ajay M. Shah, Richard J. B. Dobson, Paul A. Scott. Semantic computational analysis of anticoagulation use in atrial fibrillation from real world data. Accepted/In press: PLoS ONE. 2019. doi:10.1371/journal.pone.0225625 Available at: medRxiv

• Honghan Wu, Karen Hodgson, Sue Dyson, Katherine I. Morley, Zina M. Ibrahim, Ehtesham Iqbal, Robert Stewart, Richard JB Dobson, Cathie Sudlow. Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding Approach. JMIR Med Inform 2019;7(4):e14782. DOI:10.2196/14782 PMID: 31845899. 2019

• Gorinski, Philip John and Wu, Honghan and Grover, Claire and Tobin, Richard and Talbot, Conn and Whalley, Heather and Sudlow, Cathie and Whiteley, William and Alex, Beatrice. Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches. In Proceedings: Second UK Healthcare Text Analytics Conference. arXiv:1903.03985. 2019

2018

• Jackson, Richard, Ismail Kartoglu, Clive Stringer, Genevieve Gorrell, Angus Roberts, Xingyi Song, Honghan W et al. “CogStack-experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital.” BMC medical informatics and decision making 18, no. 1 (2018): 47. 10.1186/s12911-018-0623-9

• Honghan Wu, Giulia Toti, Katherine I Morley, Zina Ibrahim, Amos Folarin, Ismail Kartoglu, Richard Jackson, Asha Agrawal, Clive Stringer, Darren Gale, Genevieve M Gorrell, Angus Roberts, Matthew Broadbent, Robert Stewart, Richard J B Dobson. SemEHR: A General-purpose Semantic Search System to Surface Semantic Data from Clinical Notes for Tailored Care, Trial Recruitment and Clinical Research. Journal of the American Medical Informatics Association, Volume 25, Issue 5, 1 May 2018, Pages 530–537, cx160, 2018. doi:10.1093/jamia/ocx160

2017

• Daniel M. Bean, Honghan Wu, Olubanke Dzahini, Matthew Broadbent, Robert Stewart & Richard J. B. Dobson. Knowledge graph prediction of unknown adverse drug reactions and validation in electronic health records. Scientific Reports, Article number: 16416 (2017) doi:10.1038/s41598-017-16674-x

• Honghan Wu, Anika Oellrich, Christine Girges, Bernard de Bono, Tim J.P. Hubbard, Richard J.B. Dobson. Automated PDF highlighting to support faster curation of literature for Parkinson’s and Alzheimer’s disease. Database (Oxford) 2017; 2017 (1): bax027. DOI: 10.1093/database/bax027

• Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu (Editors) Exploiting Linked Data and Knowledge Graphs for Large Organisations. Springer International Publishing. 2017. ISBN: 978-3-319-45652-2. DOI: 10.1007/978-3-319-45654-6 Available at: Springer (Edited Book)

• Gomez-Perez, Jose Manuel, Jeff Z. Pan, Guido Vetere, and Honghan Wu. 2017. “Enterprise Knowledge Graph: An Introduction.” In Exploiting Linked Data and Knowledge Graphs in Large Organisations, edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu, 1-14. Cham: Springer International Publishing. DOI: 10.1007/978-3-319-45654-6_1

• Villazon-Terrazas, Boris, Nuria Garcia-Santa, Yuan Ren, Alessandro Faraotti, Honghan Wu, Yuting Zhao, Guido Vetere, and Jeff Z. Pan. 2017. “Knowledge Graph Foundations.” In Exploiting Linked Data and Knowledge Graphs in Large Organisations, edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu, 17-55. Cham: Springer International Publishing. DOI: 10.1007/978-3-319-45654-6_2

• Denaux, Ronald, Yuan Ren, Boris Villazon-Terrazas, Panos Alexopoulos, Alessandro Faraotti, and Honghan Wu. 2017. “Knowledge Architecture for Organisations.” In Exploiting Linked Data and Knowledge Graphs in Large Organisations, edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu, 57-84. Cham: Springer International Publishing. DOI: 10.1007/978-3-319-45654-6_3

• Wu, Honghan, Ronald Denaux, Panos Alexopoulos, Yuan Ren, and Jeff Z. Pan. 2017. “Understanding Knowledge Graphs.” In Exploiting Linked Data and Knowledge Graphs in Large Organisations, edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu, 147-180. Cham: Springer International Publishing. DOI: 10.1007/978-3-319-45654-6_6

• Moschitti, Alessandro, Kateryna Tymoshenko, Panos Alexopoulos, Andrew Walker, Massimo Nicosia, Guido Vetere, Alessandro Faraotti, Marco Monti, Jeff Z. Pan, Honghan Wu, and Yuting Zhao. 2017. “Question Answering and Knowledge Graphs.” In Exploiting Linked Data and Knowledge Graphs in Large Organisations, edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu, 181-212. Cham: Springer International Publishing. DOI: 10.1007/978-3-319-45654-6_7

• Pan, Jeff Z., Jose Manuel Gomez-Perez, Guido Vetere, Honghan Wu, Yuting Zhao, and Marco Monti. 2017. “Enterprise Knowledge Graph: Looking into the Future.” In Exploiting Linked Data and Knowledge Graphs in Large Organisations, edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez and Honghan Wu, 237-249. Cham: Springer International Publishing. DOI: 10.1007/978-3-319-45654-6_9

• Iqbal, Ehtesham; Mallah, Robbie; Rhodes, Daniel; Wu, Honghan; Romero, Alvin; Chang, Nynn; Dzahini, Olubanke; Pandey, Chandra; Broadbent, Matthew; Stewart, Robert; Dobson, Richard J. B.; Ibrahim, Zina M.; Groza, Tudor (Editor). ADEPt, a semantically-enriched pipeline for extracting adverse drug events from free-text electronic health records. PLoS One , Vol. 12, No. 11, 11.2017, p. e0187121. doi:10.1371/journal.pone.0187121