Dr Karin Slater PhD

Dr Karin Slater

Institute of Cancer and Genomic Sciences
Assistant Professor of Biomedical Semantics

Contact details

Address
Institute of Cancer and Genomic Sciences
Haworth Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr. Slater serves as an Assistant Professor of Biomedical Semantics. She is deeply passionate about exploring semantic techniques to create and analyse functionally linked data. Her ultimate aim is to derive actionable insights that produce real-world impacts across a variety of scientific disciplines.

Qualifications

  • PhD in Computational Biology, 2020
  • Bsc (Hons) in Open Source Computing, Aberystwyth University, 2015

Teaching

Research

Research Interests

  • Ontology and ontology accessories
  • Functionally linked data
  • FAIRification
  • Semantic methods and analysis
  • Machine learning (ML)
  • Natural language processing (NLP)
  • Knowledge graphs 

Current Projects

  • Exploring multi-contextual representations of biomedical entities
  • Semantic solutions for chemical risk assessment and environmental health
  • Multi-modal information extraction and analysis for clinical applications
  • Exploring scientific knowledge provenance

 Note: Also credited in publications as LT Slater 

Google Scholar Profile

Publications

Recent publications

Article

BigData@Heart Consortium and the cardAIc group 2023, 'Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare: artificial intelligence framework', European Heart Journal, vol. 44, no. 9, pp. 713–725. https://doi.org/10.1093/eurheartj/ehac758

Maier, D, Exner, TE, Papadiamantis, AG, Ammar, A, Tsoumanis, A, Doganis, P, Rouse, I, Slater, LT, Gkoutos, GV, Jeliazkova, N, Ilgenfritz, H, Ziegler, M, Gerhard, B, Kopetsky, S, Joshi, D, Walker, L, Svendsen, C, Sarimveis, H, Lobaskin, V, Himly, M, Van rijn, J, Winckers, L, Millán acosta, J, Willighagen, E, Melagraki, G, Afantitis, A & Lynch, I 2023, 'Harmonising knowledge for safer materials via the “NanoCommons” Knowledge Base', Frontiers in Physics, vol. 11, 1271842. https://doi.org/10.3389/fphy.2023.1271842

Slater, LT, Williams, JA, Schofield, PN, Russell, S, Pendleton, SC, Karwath, A, Fanning, H, Ball, S, Hoehndorf, R & Gkoutos, GV 2023, 'Klarigi: characteristic explanations for semantic biomedical data', Computers in Biology and Medicine, vol. 153, 106425. https://doi.org/10.1016/j.compbiomed.2022.106425

Aziz, F, Slater, LT, Bravo-Merodio, L, Acharjee, A & Gkoutos, GV 2023, 'Link prediction in complex network using information flow', Scientific Reports, vol. 13, no. 1, 14660. https://doi.org/10.1038/s41598-023-41476-9

Slater, LT, Russell, S, Makepeace, S, Carberry, A, Karwath, A, Williams, JA, Fanning, H, Ball, S, Hoehndorf, R & Gkoutos, GV 2022, 'Evaluating semantic similarity methods for comparison of text-derived phenotype profiles', BMC Medical Informatics and Decision Making, vol. 22, no. 1, 33. https://doi.org/10.1186/s12911-022-01770-4

Maruszczyk, K, Aiyegbusi, OL, Roth Cardoso, V, Gkoutos, G, Slater, L, Collis, P, Keeley, T & Calvert, M 2022, 'Implementation of patient-reported outcome measures in real-world evidence studies: analysis of ClinicalTrials.gov records (1999-2021)', Contemporary Clinical Trials, vol. 120, 106882. https://doi.org/10.1016/j.cct.2022.106882

Slater, LT, Bradlow, W, Motti, DF, Hoehndorf, R, Ball, S & Gkoutos, GV 2021, 'A fast, accurate, and generalisable heuristic-based negation detection algorithm for clinical text', Computers in Biology and Medicine, vol. 130, 104216. https://doi.org/10.1016/j.compbiomed.2021.104216

Pendleton, SC, Slater, LT, Karwath, A, Gilbert, RM, Davis, N, Pesudovs, K, Liu, X, Denniston, AK, Gkoutos, GV & Braithwaite, T 2021, 'Development and application of the ocular immune-mediated inflammatory diseases ontology enhanced with synonyms from online patient support forum conversation', Computers in Biology and Medicine, vol. 135, 104542. https://doi.org/10.1016/j.compbiomed.2021.104542

Slater, LT, Karwath, A, Hoehndorf, R & Gkoutos, GV 2021, 'Effects of negation and uncertainty stratification on text-derived patient profile similarity', Frontiers in digital health, vol. 3, 781227. https://doi.org/10.3389/fdgth.2021.781227

Carr, E, Bendayan, R, Bean, D, Stammers, M, Wang, W, Zhang, H, Searle, T, Kraljevic, Z, Shek, A, Phan, HTT, Muruet, W, Gupta, RK, Shinton, AJ, Wyatt, M, Shi, T, Zhang, X, Pickles, A, Stahl, D, Zakeri, R, Noursadeghi, M, O'Gallagher, K, Rogers, M, Folarin, A, Karwath, A, Wickstrøm, KE, Köhn-Luque, A, Slater, L, Cardoso, VR, Bourdeaux, C, Holten, AR, Ball, S, McWilliams, C, Roguski, L, Borca, F, Batchelor, J, Amundsen, EK, Wu, X, Gkoutos, GV, Sun, J, Pinto, A, Guthrie, B, Breen, C, Douiri, A, Wu, H, Curcin, V, Teo, JT, Shah, AM & Dobson, RJB 2021, 'Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study', BMC medicine, vol. 19, no. 1, 23. https://doi.org/10.1186/s12916-020-01893-3

Slater, LT, Bradlow, W, Ball, S, Hoehndorf, R & Gkoutos, GV 2021, 'Improved characterisation of clinical text through ontology-based vocabulary expansion', Journal of Biomedical Semantics, vol. 12, no. 1, 7. https://doi.org/10.1186/s13326-021-00241-5

Slater, LT, Williams, JA, Karwath, A, Fanning, H, Ball, S, Schofield, PN, Hoehndorf, R & Gkoutos, GV 2021, 'Multi-faceted semantic clustering with text-derived phenotypes', Computers in Biology and Medicine, vol. 138, 104904. https://doi.org/10.1016/j.compbiomed.2021.104904

Karwath, A, Bunting, KV, Gill, SK, Tica, O, Pendleton, S, Aziz, F, Barsky, AD, Chernbumroong, S, Duan, J, Mobley, AR, Cardoso, VR, Slater, L, Williams, JA, Bruce, E, Wang, X, Flather, MD, Coats, AJS, Gkoutos, GV & Kotecha, D 2021, 'Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis', The Lancet, vol. 2021, no. 10309, pp. 1-9. https://doi.org/10.1016/s0140-6736(21)01638-x

Preprint

Slater, LT, Russell, S, Makepeace, S, Carberry, A, Karwath, A, Williams, JA, Fanning, H, Ball, S, Hoehndorf, R & Gkoutos, GV 2021 'Evaluating semantic similarity methods for comparison of text-derived phenotype profiles' medRxiv. https://doi.org/10.1101/2021.08.08.21261762

Review article

Wu, H, Wang, M, Wu, J, Francis, F, Chang, Y-H, Shavick, A, Dong, H, Poon, MTC, Fitzpatrick, N, Levine, AP, Slater, LT, Handy, A, Karwath, A, Gkoutos, GV, Chelala, C, Shah, AD, Stewart, R, Collier, N, Alex, B, Whiteley, W, Sudlow, C, Roberts, A & Dobson, RJB 2022, 'A survey on clinical natural language processing in the United Kingdom from 2007 to 2022', NPJ digital medicine, vol. 5, no. 1, 186. https://doi.org/10.1038/s41746-022-00730-6

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