Arlene Casey

Dunhill Medical Trust Senior Research Fellow

Biography

Background

Arlene is a Dunhill Medical Trust Senior Research Fellow

After earning her BSc (Hons) in Mathematics for Business Analysis, Arlene spent 18 years in industry, primarily in pharmaceutical research. During this time, she developed advanced analytical and software development skills while building a strong foundation in data infrastructure, management, and regulatory-compliant processes for large-scale data handling in drug and medical device development.

She later returned to academia, specialising in Natural Language Processing (NLP) and earning a PhD from the University of Edinburgh in 2020. Her expertise lies at the intersection of informatics research and applied data science, with a focus on leveraging NLP and machine learning to extract valuable insights from complex health data.

Currently, her team focuses on two key areas:

  1. Developing innovative algorithms that enable the responsible use of unstructured health data, ensuring regulatory compliance while maximizing research potential.
  2. Applying NLP to derive meaningful insights from health data, with the goal of uncovering hidden patterns and indicators that enhance our understanding of aging and mental well-being.

Qualifications

B.Sc (Hons), M.Sc (distinction), PhD

Responsibilities & affiliations

NLP Programme Lead and Principal NLP Data Scientist, DataLoch

Postgraduate teaching

Course Leader: MSc Data Science for Health and Social Care. Foundation in NLP for Health & Social Care

Open to PhD supervision enquiries?

Yes

Research summary

I specialise in Natural Language Processing (NLP) with a focus on developing innovative algorithms that enable the responsible use of unstructured health data in secure environments. My work ensures regulatory compliance while maximizing the research potential of complex health data.

My primary research interest lies in later-life health and mental health, where I apply advanced NLP and data-driven methodologies to uncover meaningful insights. By identifying hidden patterns and key indicators, I aim to enhance our understanding of aging, mental well-being, and associated risks, ultimately driving improvements in healthcare and policy.

With a strong foundation in industry-based research, my expertise sits at the intersection of informatics research and applied data science. I am deeply passionate about collaboration and knowledge sharing, working to bridge the gap between research and real-world application. My goal is to empower a broader community of scientists, clinicians, and policymakers by making data-driven discoveries accessible and impactful, fostering innovation for meaningful change.

Current project grants

Casey A (Personal Fellowship) 'Improving prediction in later life syndromes by unlocking hidden information in clinical free-text' Dunhill Medical Trust Senior Proleptic Fellowship, October 2023 -2028, £292,090

Past project grants

Casey A (PI) ‘SARA: Semi-Automated Risk Assessment of Data Provenance and Clinical Free Text in TREs’, DARE UK Driver Project, Feb23-Oct-23 £478,762

Casey A (PI) ‘Enhancing the data landscape: Exploring de-identification of narrative EHRs, Research data Scotland, Nov 2022- October 2023, £170,000

Casey A (Co-PI) ‘Developing public engagement and co-design skills with health data researchers: A case study on co-designing networks of care in rural communities’, Wellcome Institutional Strategic Support Fund, Jan 2022-Dec 2022, £11,840

Casey A (PI) ‘Talking telephone Boxes’, Innovation Initiative Grant, University of Edinburgh, October 2018, £4,500

Conference details

Healthcare Text Analytics Conference (HealTAC) - currently serve on the Programme committee and  Conference Co-Chair for HealTAC 2025 (Glasgow).

 

Scottish Health innovation Conference 2023 - Best Oral Presentation Award.

Alan Turing post-doctoral enrichment award: 'Collaborative workshop to share knowledge and develop novel methodologies for innovative and safe ways to provision free-text EHR use in Trusted Research Environments for NLP development', 2022 £2,000

Scottish International Education Trust, PhD Research Support, 2018 £1,500 

Best Student Paper award: Noushahr, H. G., Ahmadi, S., Casey, A., Fast Handwritten Digit Recognition with Multilayer Ensemble Extreme Learning Machine, SGAI Conference, (2015)

2013 U.K. Data Centre solutions award for public sector project of the year. 

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