Laura Moss

Research & Development Healthcare Computer Scientist,
NHS Greater Glasgow & Clyde

Honorary Senior Lecturer,
School of Medicine, University of Glasgow

Dr Laura Moss is a Computer Scientist in the Department of Clinical Physics and Bioengineering at NHS Greater Glasgow & Clyde. Dr Moss' principal research field is knowledge engineering and the semantic web, specifically the capture, representation and subsequent refinement of knowledge for use in intelligent medical systems. Dr Moss gained a PhD from the University of Aberdeen in 2010 for work on an approach to the refinement of semantic web knowledge bases, comprising the automatic generation of explanations for anomalies and analogical reasoning. This work was evaluated in the Critical Care medical field. She then moved to NHS Greater Glasgow & Clyde where she became a member of the IDEAS (Intelligent Data Exploration and Analysis) research group, and is currently responsible for leading research into the artificial intelligence fields of knowledge capture & refinement for decision support, hypothesis generation, and intelligent data analysis. In addition, she is a member of the European BrainIT research group and works in collaboration with several external research groups. She has extensive experience of working within multidisciplinary teams. Dr Moss holds honorary research positions in the School of Medicine, University of Glasgow, and Department of Computing Science, University of Aberdeen

CHART-ADAPT: Connecting Healthcare And Research Through A Data Analysis Provisioning Technology

Main Collaborators:

Semantic Web Approach to Assessing Medical Data Quality

Main Collaborators:

Argumentation Logic for the Explanation of Medical Anomalies

Main Collaborators:

Detection and Removal of Inconsistencies (or Biases) during Knowledge Capture.

Main Collaborators:

Remote Positional Monitoring of Critical Care Patients

Main Collaborators:

Intelligent Data Analysis

Main Collaborator:

PhD Thesis: Explaining Anomalies: An Approach to Anomaly-Driven Revision of a Theory

During my PhD I investigated the use of domain knowledge represented in ontologies as a method of generating domain acceptable knowledge base refinements. The use of ontologies avoids the requirement for large datasets and can lead to sophisticated refinements previously unavailable. In the first stage, I investigated the automatic explanation of anomalies as a method of generating refinements to a theory held by a human or computer. Anomalies are interesting as they help to identify the part of the theory requiring refinement. This work involved extensive interviews held with domain experts and the strategies used by the domain experts to provide (appropriate) explanations for the anomalies were identified. A knowledge-based system, EIRA (Explaining, Inferencing, and Reasoning about Anomalies), was developed. EIRA implemented the domain-expert based strategies with domain ontologies and data to automatically generate explanations for an anomaly. To evaluate this approach, EIRA has been applied in the Intensive Care Unit (ICU) domain to investigate the detection and explanation of anomalous patient responses to treatment and ICU clinicians have evaluated the explanations produced by EIRA. In the second stage of my PhD work I explored the application of analogical reasoning in conjunction with domain ontologies to generate refinements.

Peer Reviewed Publications

  1. Depreitere B. et al. (2018) Cerebral Perfusion Pressure Variability Between Patients and Between Centres. In: Heldt T. (eds) Intracranial Pressure & Neuromonitoring XVI. Acta Neurochirurgica Supplement, vol 126. Springer, Cham. doi:10.1007/978-3-319-65798-1_1. PMID:29492521
  2. Hawthorne C., Shaw M., Piper I., Moss L., Kinsella J. (2018) Transcranial Bioimpedance Measurement as a Non-invasive Estimate of Intracranial Pressure. In: Heldt T. (eds) Intracranial Pressure & Neuromonitoring XVI. Acta Neurochirurgica Supplement, vol 126. Springer, Cham. doi:10.1007/978-3-319-65798-1_19 PMID: 29492539
  3. Flechet M. et al. (2018) Visualizing Cerebrovascular Autoregulation Insults and Their Association with Outcome in Adult and Paediatric Traumatic Brain Injury. In: Heldt T. (eds) Intracranial Pressure & Neuromonitoring XVI. Acta Neurochirurgica Supplement, vol 126. Springer, Cham. doi:10.1007/978-3-319-65798-1_57. PMID: 29492577
  4. Shaw M., Moss L., Hawthorne C., Kinsella J., Piper I. (2018) Investigation of the Relationship Between the Burden of Raised ICP and the Length of Stay in a Neuro-Intensive Care Unit. In: Heldt T. (eds) Intracranial Pressure & Neuromonitoring XVI. Acta Neurochirurgica Supplement, vol 126. Springer, Cham. doi: 10.1007/978-3-319-65798-1_42. PMID: 29492562
  5. Piper I., Shaw M., Hawthorne C., Kinsella J, Moss L. (2018) Medical Waveform Format Encoding Rules Representation of Neurointensive Care Waveform Data. In: Heldt T. (eds) Intracranial Pressure & Neuromonitoring XVI. Acta Neurochirurgica Supplement, vol 126. Springer, Cham. doi: 10.1007/978-3-319-65798-1_38. PMID: 29492558
  6. Stell A., Piper I. and Moss L. (2018). Automated Measurement of Adherence to Traumatic Brain Injury (TBI) Guidelines using Neurological ICU Data. In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, ISBN 978-989-758-281-3, pages 135-146. doi: 10.5220/0006583801350146
  7. Dewanti, A., Papapanagiotou, P., Gilhooly, C., Fleuriot, J., Manataki, A., Moss, L.. Development of Workflow-Based Guidelines for the Care of Burns in Scotland. Proceedings of the International Conference e-Health 2017, ISBN:978-989-8533-65-4, pages 155-158.
  8. Guiza, F., Meyfroit, G., Piper, I., Citerio, G., Chambers, I., Enblad, P., Nillson, P., Feyen, B., Jorens, P., Maas, A., Schuhmann, M.U., Donald, R., Moss, L., Van den Berghe, G., Depreitere, B. (2017) Cerebral Perfusion Pressure Insults and Associations with Outcome in Adult Traumatic Brain Injury. J Neurotrauma Aug 15; 34(16): 2425-2431. doi:10.1089/neu.2016.4807). PMID:28385097
  9. Moss, L., Shaw, M., Piper, I., Hawthorne, C., Kinsella, J. (2017) Sharing of Big Data in Healthcare: Public Opinion, Trust, and Privacy Considerations for Health Informatics Researchers. In: Proc. of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017). ISBN 978-989-758-213-4 pages 463-468, doi:10.5220/0006251504630468
  10. Moss, L., Shaw, M., Piper, I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. (2016) Apache Spark for the Analysis of High Frequency Neurointensive Care Unit Data: Preliminary Comparison of Scala vs. R. In: Proc. of American Medical Informatics Association 2016 Annual Symposium (AMIA 2016) pages 1523.
  11. Moss, L., Shaw, M., Piper, I., Arvind, D.K., Hawthorne, C. (2016) In: Ang BT. (eds) Intracranial Pressure and Brain Monitoring XV. Acta Neurochirurgica Supplement, vol 122. Springer, Chamdoi: doi:10.1007/978-3-319-22533-3_52.
  12. Sim, M., Moss, L., Sleeman, D., Kinsella, J. (2015) Knowledge Capture Techniques to Design a Score of Overall Physiological State in Critical Illness. Critical Care Medicine 43(12):1-3, December. doi:10.1097/01.ccm.0000473972.12234.b0
  13. Bonner, S., A.S. McGough,., Kureshi, I., Brennan, J., Theodoropoulos, G., Moss, L., Corsar, D., Antoniou, G. (2015) Data Quality Assessment and Anomaly Detection Via Map / Reduce and Linked Data: A Case Study in the Medical Domain. 2015 IEEE International Conference on Big Data (Big Data), pp. 737-746. doi: 10.1109/BigData.2015.7363818
  14. Guiza, F., Depreitere, B., Piper, I., Citerio, G., Chambers, I., Jones, P,A., Lo, T.Y., Enblad, P., Nillson, P., Feyen, B., Jorens, P., Maas, A., Schuhmann, M.U., Donald, R., Moss, L., Van den Berghe, G., Meyfroidt, G. (2015) Visualizing the Pressure and Time Burden of Intracranial Hypertension in Adult and Paediatric Traumatic Brain Injury. Intensive Care Med, Jun;41(6):1067-76. doi: 10.1007/s00134-015-3806-1. PMID:25894624
  15. Moss. L., Corsar, D., Hawthorne, C., Piper, I., Shaw, M., Kinsella, J. (2014) Data Quality in Neurointensive Care Datasets. Critical Care Medicine, Dec 2014, Vol 42 (12) pA1496. doi: 10.1097/01.ccm.0000458064.02118.7b
  16. Bonner, S., Antoniou., G., Moss, L., Kureshi, I., Corsar, D., Tachmazidis, I. (2014) Using Hadoop to Implement a Semantic Method of Assessing The Quality of Research Medical Datasets. BigDataScience '14: Proceedings of the 2014 International Conference on Big Data Science and Computing. ACM Press, 2014. doi: 10.1145/2640087.2644163
  17. Stell, A., Moss, L., Piper, I. (2014) Building an Empirical Treatment Protocol from High-Resolution Traumatic Brain Injury Data. In: Warren J., Gray K. (eds) HIKM '14 Proceedings of the Seventh Australasian Workshop on Health Informatics and Knowledge Management, Vol 153, Austrailian Computer Society. ISBN: 978-1-921770-35-7 pages 79-88.
  18. Tober, K., Moss, L., Runcie, A., Willox, L., Talwar, D., Kinsella, J. (2013) Asymmetric Dimethylarginine, Homoarginine Levels and Atrial Fibrillation in Oesophagectomy Patients, Critical Care Medicine, Dec 2013, Vol 41(12)
  19. Moss, L., Corsar, D., Piper, I., Kinsella, J. (2013) A Semantic Web Approach to Assessing the Quality of Medical Data. In: Proceedings of BCS Health Informatics Scotland Conference 2013 (Edinburgh, UK)
  20. Moss, L., Corsar, D., Piper, I., Kinsella, J. (2013) Trusting Intensive Care Unit (ICU) Medical Data: A Semantic Web Approach. In: Peek N., Marin Morales R., Peleg M. (eds) Artificial Intelligence in Medicine. AIME 2013. Lecture Notes in Computer Science, vol 7885. Springer, Berlin, Heidelberg. ISBN: 978-3-642-38325-0 doi.org/10.1007/978-3-642-38326-7_10
  21. Grando, A., Moss, L., Sleeman, D., Kinsella, J. (2013) Argumentation-Logic for Creating and Explaining Medical Hypotheses. Artif Intell Med, May;58(1):1-13. doi:10.1016/j.artmed.2013.02.003. PMID: 23522940
  22. Kearns, R.J., Moss, L., Kinsella, J. (2013) A Comparison of Clinical Practice Guidelines for Proximal Femoral Fracture. Anaesthesia, 2013 Feb;68(2):159-66. doi: 10.1111/anae.12076. PMID:23121498.
  23. Grando, A., Moss, L., Bel-Enguix G, Jimenez-Lopez, M.D., Kinsella, J. (2013) Argumentation-Based Dialogue Systems for Medical Training. In: Neustein A., Markowitz J. (eds) Where Humans Meet Machines. Springer, New York, NY. ISBN: 978-1-4614-6933-9. doi:10.1007/978-1-4614-6934-6_10
  24. Docking, R., Moss, L., Sim, M., Sleeman, D., Kinsella, J. Investigation into Haemodynamic Stability During Intermittent Haemodialysis in the Critically Ill. Crit Care (2012) 16(Suppl 1): P371. https://doi.org/10.1186/cc10978
  25. Docking, R., Moss, L., Sim, M, Sleeman, D., Kinsella, Investigation into the Effects of Commencing Haemodialysis in the Critically Ill. J. Crit Care (2012) 16(Suppl 1): P359. https://doi.org/10.1186/cc10966.
  26. Sleeman, D., Moss, L., Aitken, A., Hughes, M., Sim, M., Kinsella, J. Detecting and Resolving Inconsistencies between Domain Experts' Different Perspectives on (Classification) Tasks. Artificial Intelligence in Medicine, 2012 Jun;55(2):71-86. doi: 10.1016/j.artmed.2012.03.001. PMID:22483422
  27. Moss, L., Corsar, D., Piper, I. (2012) A Linked Data Approach to Assessing Medical Data. In: Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2012), pages 529-532, IEEE. doi: 10.1109/CBMS.2012.6266391
  28. Stell, A., Moss, L., Piper, I. (2012) Knowledge-Driven Inference of Medical Interventions. In: Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2012), pages 521-524, IEEE. doi: 10.1109/CBMS.2012.6266389
  29. Moss, L, Sleeman, D., Quasim, T., Sim, M., Booth, M., Puxty, A., Kinsella, J. Identifying Myocardial Damage from Routinely Recorded Data in the Intensive Care Unit (ICU). Intensive Care Medicine, 37(Suppl 1): 1. https://doi.org/10.1007/s00134-011-2322-1
  30. Grando, A., Moss, L., Glasspool, D., Sleeman, D., Sim, M., Kinsella, J. (2011) Argumentation-Logic for Explaining Anomalous Patient Responses to Treatments. In: Peleg M., Lavrac N., Combi C. (eds) Artificial Intelligence in Medicine. AIME 2011. Lecture Notes in Computer Science, vol 6747. Springer, Berlin, Heidelberg. ISBN:978-3-642-22217-7 doi:10.1007/978-3-642-22218-4_5.
  31. Sleeman, D., Moss, L., Sim, M., Kinsella, J. (2011) Predicting Adverse Events: Detecting Myocardial Damage in Intensive Care Unit (ICU) Patients. In: Proc. of The Sixth International Conference on Knowledge Capture ACM Press, New York,NY,USA 73-80. ISBN: 978-1-4503-0396-5. doi: 10.1145/1999676.1999690
  32. Sleeman, D., Moss, L., Gyftodimos, E., Nicolson, M., Devereux G. (2010) A Comparison between Clinical Decisions made about Lung Cancer Patients and those inherent in the corresponding Scottish Intercollegiate Guideline Network (SIGN) Guideline, Health Informatics J. 2010 Dec;16(4):260-73. doi: 10.1177/1460458210380520. PMID:21216806
  33. Moss, L., Sleeman, D., Sim, M. (2010) Reasoning by Analogy in the Generation of Domain Acceptable Ontology Refinements. In: Cimiano P., Pinto H.S. (eds) Knowledge Engineering and Management by the Masses. EKAW 2010. Lecture Notes in Computer Science, vol 6317. Springer, Berlin, Heidelberg. ISBN:978-3-642-16437-8. doi: 10.1007/978-3-642-16438-5_43
  34. Sleeman, D., Aitken, A., Moss, L., Kinsella, J., Sim, M. (2010) A System to Detect Inconsistencies between a Domain Expert's Different Perspectives on (Classification) Tasks. In: Koronacki J., Ra? Z.W., Wierzcho? S.T., Kacprzyk J. (eds) Advances in Machine Learning II. Studies in Computational Intelligence, vol 263. Springer, Berlin, Heidelberg. ISBN:978-3-642-05178-4. doi:10.1007/978-3-642-05179-1_14.
  35. Moss, L., Sleeman, D., Sim, M., Booth, M., Daniel, M., Donaldson, L., Gilhooly, C., Hughes, M., Kinsella, J. (2010) Ontology-Driven Hypothesis Generation to Explain Anomalous Patient Responses to Treatment. Knowledge Based Systems, Volume 23, Issue 4, May 2010, pages 309-315. doi: doi.org/10.1016/j.knosys.2009.11.009.
  36. Sim, M., Aitken, A., Moss, L., Sleeman, D., Kinsella, J. Confusion Matrices To Refine A Novel Scoring System For Cardiovascular Instability In Intensive Care. Scottish Medical Journal, Volume 54, Issue 2, pg 56, May 2009
  37. Moss, L., Sleeman, D., Sim, M., Booth, M., Daniel, M., Donaldson, L., Gilhooly, C., Hughes, M., Kinsella, J. Ontology-Driven Hypothesis Generation to Explain Anomalous Patient Responses to Treatment. (2010) Ontology-Driven Hypothesis Generation to Explain Anomalous Patient Responses to Treatment. In: Bramer M., Ellis R., Petridis M. (eds) Research and Development in Intelligent Systems XXVI. Springer, London pages 63-76. ISBN:978-1-84882-982-4. doi: 10.1007/978-1-84882-983-1_5 *Best Student Paper*
  38. Corsar, D., Moss, L., Sleeman, D., Sim, M.(2009) Supporting the Development of Medical Ontologies. Frontiers in Artificial Intelligence and Applications: Formal Ontologies Meet Industry, pages 114-125. IOS Press. ISBN:978-1-60750-047-6.
  39. Moss, L., Sleeman, D., Booth, M., Daniel, M., Donaldson, L., Gilhooly, C., Hughes, M., Sim, M., Kinsella, J. (2009) Explaining Anomalous Responses to Treatment in the Intensive Care Unit. In: Combi C., Shahar Y., Abu-Hanna A. (eds) Artificial Intelligence in Medicine. AIME 2009. Lecture Notes in Computer Science, vol 5651. Springer, Berlin, Heidelberg. ISBN:978-3-642-02975-2. doi:10.1007/978-3-642-02976-9_36.
  40. Moss, L., Sleeman, D., Kinsella, J., Sim, M. (2008) ACHE: an Architecture for Clinical Hypothesis Examination. In: Puurone S., Pechenizkiy M., Tsymbal A.,Jye Lee D (eds) Proceedings of the 21st IEEE Symposium on Computer-Based Medical Systems (CBMS 2008) pages 158-160, IEEE. ISBN:978-0-7695-3165-6. doi:10.1109/CBMS.2008.100.
  41. Gyftodimos, E., Moss, L., Sleeman, D., Welch, A. (2008) Analysing PET Scans Data for Predicting Response to Chemotherapy in Breast Cancer Patients. In: Ellis R., Allen T., Petridis M. (eds) Applications and Innovations in Intelligent Systems XV. SGAI 2007. Springer, London. ISBN:978-1-84800-085-8. doi:10.1007/978-1-84800-086-5_5.
  42. Sleeman, D., Fluck, N., Gyftodimos, E., Moss, L., Christie, G. (2007) An Intelligent Aide for Interpreting a Patient's Dialysis Data Set. In: Bellazzi R., Abu-Hanna A., Hunter J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science, vol 4594. Springer, Berlin, Heidelberg. ISBN:978-3-540-73598-4. doi:10.1007/978-3-540-73599-1_7.

Conference Abstracts and Posters

  1. Moss, L., Hawthorne, C., Shaw, M., Piper, I., Aridhia, Philips Healthcare, Kinsella, J. Is There an Age Divide in Opinions about the Sharing of Critical Care Data with Private Companies? Society of Critical Care Medicine (SCCM) 47th Critical Care Congress, San Antonio, Texas, USA, February 2018.
  2. Kinsella, J., Hawthorne, C., Shaw, M., Piper, I., Philips Healthcare, Aridhia, Moss, L. Public Perception of the Collection and Use of Critical Care Patient Data Beyond Treatment: a Pilot Study. Society of Critical Care Medicine (SCCM) 46th Critical Care Congress, Honolulu, Hawaii, USA, January 2017.
  3. Shaw, M., Hawthorne, C., Moss, L., Piper, I., Kinsella, J., Philips Healthcare, Aridhia. Investigation of an Improved Optimal Cerebral Perfusion Pressure Calculation Methodology. Society of Critical Care Medicine (SCCM) 46th Critical Care Congress, Honolulu, Hawaii, USA, January 2017.
  4. Moss, L., Shaw, M., Hawthorne, C., Piper, I., McPeake, J., Quasim, T., Kinsella, J. Outcome in the Year Following Admission to an Intensive Care Unit in Scotland with Traumatic Brain Injury. Scottish Intensive Care Society Annual Scientific Meeting 2017, St. Andrew's, January 2017.
  5. Papapanagiotou, P., Dewanti, A., Manataki, A., Fleuriot, J., Gilhooly, C., Moss, L.,. Workflow Modelling of Burns Care Protocols. Scottish Intensive Care Society Annual Scientific Meeting 2017, St. Andrew's, January 2017.
  6. Moss, L., Shaw, M., Piper, I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Enabling Analysis of High Frequency Clinical Data at the Bedside: Update on the CHART-ADAPT Project. NHS Research Scotland Annual Conference 2016, Glasgow, UK, October 2016.
  7. Moss, L., Kinsella, J., Shaw, M., Piper, I., Hawthorne, C., Aridhia, Philips Healthcare. A Platform for the Analysis of Critical Care Data: Update on the CHART-ADAPT Project. BCS Health Informatics Scotland Conference 2016, Glasgow, UK, October 2016.
  8. Moss, L., Shaw, M., Piper, I., Hawthorne, C., Kinsella, J., Philips Healthcare., Aridhia. Pilot Evaluation of a De-Identification Tool for Neurointensive Care Unit Data. 16th International Sympoisum on Intracranial Pressure and Neuromonitoring (ICP 2016), Cambridge, Boston, USA, June 2016.
  9. Klein, S., Piper, I., Gregson, B., Enblad, P., Ragauskas, A., Citerio, G., Chambers, I., Neumann, J-O., Sahuquillo, J., Kiening, K., Moss, L., Nilsson, P., Donald, R., Howells, T., Depreitere, B. Timing of GCS Assessment and the Relationship with Long Term Outcome after Acute Traumatic Brain Injury. 16th International Sympoisum on Intracranial Pressure and Neuromonitoring (ICP 2016), Cambridge, Boston, USA, June 2016.
  10. Shaw, M., Moss, L., Piper,I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Improving the Performance Time of the Pressure Reactivity Index (PRx) Model using R and Scala. British Neurosurgical Research Group Meeting 2016, Cambridge, UK, March 2016.
  11. Shaw, M., Moss, L., Piper,I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Comparison of Hypotension Burden Models in the Neuro-intensive Care Unit. British Neurosurgical Research Group Meeting 2016, Cambridge, UK, March 2016.
  12. Moss, L.,, Shaw, M., Piper,I., Hawthorne, C., Kinsella, J., Aridhia, Philips Healthcare. Enabling Big Data Analysis in the Neurointensive Care Unit. British Neurosurgical Research Group Meeting 2016, Cambridge, UK, March 2016.
  13. Moss, L.,, Shaw, M., Hawthorne, C., Piper, I., Kinsella, J. Connecting Healthcare and Research Through A Data Provisioning Technology (CHART-ADAPT). Scottish Intensive Care Society 25th Annual Scientific Meeting. St. Andrew's, UK, January 2016.
  14. Shaw, M., Moss, L., O'Donnell, A., Judson, A., Piper, I. Exploring the Application of High Performance Computing to Enable the Analysis of Physiological Brain Injury Data. NRS (NHS Research Scotland) Conference 2015. Glasgow, UK, October 2015.
  15. Sleeman, D., Moss, L., Kinsella, J. Studies where experts provide feedback on patterns produced by a temporal discovery workbench. 1st International Workshop on Capturing Scientific Knowledge, Palisades, NY, USA, October 2015.
  16. Moss, L., Shaw, M., Piper, I, and Aridhia. Assessing the Impact of Data Modelling in Real-Time Traumatic Brain Injury Monitoring To Improve Patient Outcomes. Farr Institute International Conference 2015: Data Health Intensive Research and Care, St.Andrews, UK, August 2015.
  17. Henderson, W., Shaw, M., McLennan, F., Piper, I., Moss, L., Hawthorne, C. Cluster Analysis of the BrainIT Database. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015.
  18. Shaw, M., O'Donnell, A., Piper, I., Moss, L. Down-Sampling Traumatic Brain Injury Physiological Data Using High Performance Computing. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015.
  19. Canty, M., O'Kane, R., Turner, C., Shaw, M., Hawthorne, C., Moss, L., Piper, I. Comparison of 24 Vs 48 Hour ICP Recording for the Detection of metrics for raised ICP in Patients Investigated for CSF circulation abnormalities. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015.
  20. Shaw, M., Hawthorne, C., Moss, L., Piper, I. Improvements to the Optimal Cerebral Perfusion Pressure Calculation. British Neurosurgical Research Group Meeting 2015, Cardiff, UK, March 2015.
  21. Sleeman, D., Moss. L., Kinsella, J. Temporal Discovery Workbench: a Case Study with ICU Patient Datasets. BCS Health Informatics Scotland Conference 2014, Glasgow, UK, September 2014.
  22. Moss, L., Shaw, M., Piper, I., Arvind, D.K, Automatic Calculation of Hydrostatic Pressure Gradient in Head Injured Patients: A Pilot Study. 15th International Symposium on Intracranial Pressure and Brain Monitoring (ICP 2013), Singapore, November 2013.
  23. Moss, L., Corsar, I., Piper, I., Hawthorne, C. An Approach for Establishing the Quality of Traumatic Brain Injury Data. 15th International Symposium on Intracranial Pressure and Brain Monitoring (ICP 2013), Singapore, November 2013.
  24. Stell, A., Piper, I., Moss, L. Multi-Centre ICP Treatment Patterns: a Study of the Brain-IT Database. 15th International Symposium on Intracranial Pressure and Brain Monitoring (ICP 2013), Singapore, November 2013.
  25. Moss, L., Piper, I., Shaw, M. Ontologies, Provenance, and Speckled Computing - Research Update. Brain IT 2012, Leuven, Belgium, Dec 2012
  26. Corsar, D., Moss, L., Piper, I. Data Quality Assessment Using Linked Data: A Case Study in the Medical Domain. 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW), Galway, Ireland, October 2012. *Best Poster Prize*
  27. Moss, L., Sleeman, D., Kinsella, J. Differences in the Identification of Anomalies from Computerized Physiological Data. 1st International Workshop on Capturing and Refining Knowledge in the Medical Domain (KMED 2012), Galway, Ireland, October 2012.
  28. Moss, L., Sleeman, D., Sim, M., Kinsella, J. Using Cardiovascular Derangements to Predict Raised Troponin Levels. 1st International Workshop on Capturing and Refining Knowledge in the Medical Domain (KMED 2012), Galway, Ireland, October 2012.
  29. Sleeman, D., Rogers, S., Moss, L., Aiken, A., Kinsella, J. INSIGHT: Helping Domain Experts make their Knowledge more Consistent. 1st International Workshop on Capturing and Refining Knowledge in the Medical Domain (KMED 2012), Galway, Ireland, October 2012.
  30. Sim, M., Moss, L., Sleeman, D., Kinsella, J. A novel system for detecting myocardial damage in the critically ill patient. Society of Critical Care Medicine (SCCM) Annual Congress, Houston, Texas, USA, February 2012.
  31. Moss, L., Sleeman, D., Kinsella, J. Clinicians' perspective on the connection between myocardial damage, troponin, and cardiovascular abnormality. Scottish Intensive Care Society Annual Meeting, St.Andrews, UK, January 2012.
  32. Sleeman, D., Muniesa, M., Moss, L., Sim, M., Docking, R., Kinsella, J. Correlation between mean score of cardiovascular instability and patient outcome. Scottish Intensive Care Society Annual Meeting, St.Andrews, UK, January 2012.
  33. McLeod, C., Kearns, R., Moss, L., Kinsella, J. SIGN guideline 122 - adherence in an intensive care unit. Scottish Intensive Care Society Annual Meeting, St.Andrews, UK, January 2012.
  34. Moss, L., Sleeman, D., Quasim, T., Sim, M., Booth, M., Puxty, A., Kinsella, J. Identifying Myocardial Damage from Routinely Recorded Data in the Intensive Care Unit (ICU). European Society of Intensive Care Medicine (ESICM) LIVES Annual Congress, Berlin, Germany, October 2011.
  35. Achenyo Ogbobi, B., Kearns, R., Moss, L., Wright, F., Kinsella, J. Dysphagia following a stroke: can every patient be given a swallow test on the day of admission? Scottish Society of Physicians Annual Meeting, Dumfries, UK, September 2011.
  36. Moss, L., Piper, I., Shaw, M. Precise Pressure (PP) - Infrared Based Head Tracking in the Automatic Correction of Cerebral Perfusion Pressure Measurement. Brain IT meeting, Uppsala, Sweden, May 2011.
  37. Moss, L., Grando, M.A., Sleeman, D., Sim, M., Gilhooly, C., Kinsella, J. Formalizing and Understanding Collaborative Decision Making in the Intensive Care Unit (ICU). Scottish Intensive Care Society Annual Meeting, St.Andrews, UK, January 2011.
  38. Moss, L., Sleeman, D., Sim, M., Booth, M., Donaldson, L., Gilhooly, C., Hughes, M., Kinsella, J. Development of EIRA, a knowledge-based system to explain anomalous patient responses to treatment. BCS Health Scotland Conference, Glasgow, UK, September 2010.
  39. Moss, L., Sleeman, D., Sim, M., Booth, M., Donaldson, L., Gilhooly, C., Hughes, M., Kinsella, J. Transforming Clinical Anomalies into Clinical Insights: Developing a knowledge-based system which explains a patient's unexpected reaction to treatment. Scottish Intensive Care Society Annual Meeting, St.Andrews, January 2010
  40. Sim, M., Moss, L., Aitken, A., Kinsella, J., Sleeman, D. Intermittent Haemodialysis may be Associated with Increased Haemodynamic Stability. Scottish Intensive Care Society Annual Meeting, St.Andrews, January 2010.
  41. Gyftodimos, E., Moss, L., Sleeman, D. Welch, A. Predicting Response to Chemotherapy in Breast Cancer Patients using Machine Learning Techniques. Current Perspectives in Healthcare Computing 2007, Proceedings of the Healthcare Computing 2007 Conference (HC2007) (Harrogate, UK). The British Computer Society Health Informatics Forum
  42. Sim, M., Moss, L., Kinsella, J., Sleeman, D. Assessing Cardiovascular Status in the ICU Advances in Anaesthesia & Intensive Care Symposium, Glasgow, September 2007