N
Niels Peek
Researcher at University of Manchester
Publications - 275
Citations - 5832
Niels Peek is an academic researcher from University of Manchester. The author has contributed to research in topics: Medicine & Health care. The author has an hindex of 37, co-authored 238 publications receiving 4184 citations. Previous affiliations of Niels Peek include RMIT University & University of Amsterdam.
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Journal ArticleDOI
P052 Hydroxychloroquine retinopathy incidence in a UK specialist centre: a machine learning/natural language processing pilot study
G. Tilston,Kimme L. Hyrich,Anne Barton,Niels Peek,Ben Parker,D. William Griffiths,Jennifer Humphreys +6 more
TL;DR: In this paper , the authors used NLP to identify patients taking Hydroxychloroquine (HCQ) and determine rates of HCQ retinopathy from clinic letters in a UK tertiary Rheumatology centre.
Journal ArticleDOI
Using personas as an intermediate construct in the development of tailored messages: a case study.
TL;DR: A case study of tailoring messages to the preferences of patients with coronary heart disease illustrates the approach and shows the need for patient-centered data collection so that personas reflect patients' preferences.
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P37: Correlation of Psoriasis Disability Index and Psoriasis Area and Severity Index
Xinyi Du-Harpur,Clarisse Ganier,N. Harun,Ellie Rashidghamat,Nicholas M. Luscombe,Fiona,M. Watt,Magnus D. Lynch,W. Haw,Amaani Hussain,Jessica Nick,Reynolds,Christopher E.M. Griffiths,Niels Peek,Richard B. Warren +14 more
TL;DR: To better understand the cellular landscape of HS, in excess of 34 000 cells from lesional skin of patients with HS are sequenced, revealing striking differences both in comparison to healthy skin and to other inflammatory skin diseases such as psoriasis and eczema.
Journal ArticleDOI
Using discrete-choice experiments to elicit preferences for digital wearable health technology for self-management of chronic kidney disease
TL;DR: Investigating preferences of individuals with CKD toward wearable DHTs designed to support self-management of their condition indicates that user preferences differ between patient subgroups, supporting the case for offering a different design of the device for different patients’ strata.
Journal ArticleDOI
P38: Machine learning methods for the prediction of treatment outcome in psoriasis: a systematic review
Xinyi Du-Harpur,Clarisse Ganier,N. Harun,Ellie Rashidghamat,Nicholas M. Luscombe,Fiona,Mykaela Watt,Magnus D. Lynch,W. Haw,Amaani Hussain,Jessica Nick,Reynolds,Christopher E.M. Griffiths,Niels Peek,Richard B. Warren +14 more
TL;DR: To better understand the cellular landscape of HS, in excess of 34 000 cells from lesional skin of patients with HS are sequenced, revealing striking differences both in comparison to healthy skin and to other inflammatory skin diseases such as psoriasis and eczema.