Dr Pete Arnold

• A study of the impact of the socio-economic, educational and demographic characteristics of people with Multiple Sclerosis (MS) on the time to diagnosis. (current)

  PhD

  Other supervisor: Dr Ana Sergio Da Silva

• PM-272 Introduction to Health Data Science

  This module introduces the fundamental principles and methods of health data science. Students will gain an appreciation of the increasingly prominent role of the health data science in research and clinical application.

• PM-272C Cyflwyniad i Wyddor Data Iechyd

  Mae'r modiwl hwn yn cyflwyno egwyddorion a dulliau sylfaenol gwyddor data iechyd. Bydd myfyrwyr yn meithrin dealltwriaeth o'r rôl gynyddol bwysig sydd gan wyddor data iechyd mewn meysydd ymchwil a chlinigol.

• PM-344 Capstone Project

  The aim of this module is to provide a capstone experience to students¿ learning, through participating in their own enquiry-based research project, with guidance from an academic supervisor. The project may be laboratory or non-laboratory based, but it will always involve a research question that is drawn from the literature, and focused on a topic relevant to the life sciences. It will ask a research question and involve the critical analysis of research findings. Students will refine their oral and written communication skills to a graduate level through an oral presentation and dissertation on their research findings and conclusions.

• PMI302 Introductory Analysis of Linked Health Data

  This module introduces the topic of linked health data analysis at an introductory to intermediate level. It fills a gap in research training opportunities by combining the principles of health care epidemiology with hands-on practical exercises in the implementation of computing solutions. The module provides students with a theoretical grounding in the classroom on each topic, followed by a training session on the corresponding computing solutions. Students use de-identified linked data files in the hands-on exercises. The computing component of the module assumes a basic familiarity with computing syntax used in programs such as SPSS, SAS, STATA or R and methods of basic statistical analysis of fixed-format data files. The main lecturers will be Professors Tom Briffa and Jane Hayward of the University of Western Australia. The module co-ordinator is Dr Peter Arnold.

• PMI602 Advanced Analysis of Linked Health Data

  This module is taught at an intermediate to advanced level and assumes that students have completed PMIM302 Introductory Analysis of Linked Health Data or have equivalent knowledge. Advanced principles of health care epidemiology are combined with hands-on practical exercises in the implementation of computing solutions. The module provides students with a theoretical grounding on each topic, followed by a training session on the corresponding computing solutions. Students use de-identified data files in the hands-on exercises. The computing component of the module assumes a basic competence in the preparation of computing syntax for programs such as SPSS, SAS, STATA or R and familiarity with the statistical analysis of linked data files at an introductory to intermediate level. The main lecturer will be Professors David Preen of the University of Western Australia. The module co-ordinator is Dr Peter Arnold.

• PMIM102 Scientific Computing and Health Care

  The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate.

• PMIM102J Scientific Computing and Health Care

  The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate.

• PMIM202 Health Data Modelling

  Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets.

• PMIM202J Health Data Modelling

  Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets.

• PMIM302 Introductory Analysis of Linked Health Data

  This module introduces the topic of linked health data analysis at an introductory to intermediate level. It fills a gap in research training opportunities by combining the principles of health care epidemiology with hands-on practical exercises in the implementation of computing solutions. The module provides students with a theoretical grounding in the classroom on each topic, followed by a training session on the corresponding computing solutions. Students use de-identified linked data files in the hands-on exercises. The computing component of the module assumes a basic familiarity with computing syntax used in programs such as SPSS, SAS, STATA or R and methods of basic statistical analysis of fixed-format data files. This CPD course will be jointly delivered by Professor David Preen from the University of Western Australia and Dr Pete Arnold from Swansea University. The module co-ordinator is Dr Peter Arnold.

• PMIM502J Health Data Visualisation

  Health data scientists often have to present their findings to a non-academic/expert audience. The objective of this module is to enable students to choose and produce appropriate visualisations of health related data using a range of media.

• PMIM702 Health Data Dissertation

  This module builds on the knowledge and skills of modules PMIM302 and PMIM602 and are pre-requisites. Students will work independently with a large scale linked data set, developing and answering a specific research question.

Pete is a local area network volunteer for the IET (Institution of Engineering and Technology) and for the Society of Research Software Engineering.