A

Adel, T; McCrory, M; Tynan, C; Thompson, A; Duncan, P (2025) Characterising and Testing the Trustworthiness of Artificial Intelligence Systems. NPL Report. MS 62

Alsuleman, M; Duncan, P; Thompson, A (2025) Screening of Atrial Fibrillation using Wearable PPG Devices – a Trustworthy and Safe AI Life Cycle Case Study. NPL Report. MS 61

G

Gregorio, J; Povey, D (2025) NPL’s Data Quality Framework and its Integration with the HVMC: A proposal for Enhancing National Programmes. NPL Report. MS 59

H

Harris, Peter; Østergaard, P F; Tabandeh, S; Söderblom, H; Kok, G; van Dijk, M; Luo, Y; Pearce, J; Tucker, D; Vedurmudi, A P; Iturrate-Garcia, M (2025) Measurement Uncertainty Evaluation for Sensor Network Metrology. Metrology, 5 (1). 3 ISSN 2673-8244

K

Klauenberg, K; Harris, P; Möhrke, P; Pennecchi, F (2025) The Three Most Common Needs for Training on Measurement Uncertainty. Measurement Science Review, 25 (5). pp. 257-275. ISSN 1335-8871

Kok, G; van Dijk, M; Harris, P; Vedurmudi, A (2025) Modelling and determining correlations in sensor networks. Measurement: Sensors, 38. 101793 ISSN 26659174

S

Somathilake, G; Ford, E; Armes, J; Moschoyiannis, S; Collins, M; Francsics, P; Lemanska, A (2025) Evaluating the quality of prostate cancer diagnosis recording in CPRD GOLD and CPRD Aurum primary care databases for observational research: A study using linked English electronic health records. Cancer Epidemiology, 94. 102715 ISSN 18777821

Somathilake, G; Lemanska, A; Armes, J; Moschoyiannis, S; Ford, E (2025) Sociodemographic Disparities in the Stage of Prostate Cancer Diagnosis in England: A Population-Based Analysis Using Linked Electronic Health Records Data. Studies in Health Technology and Informatics, 327. pp. 1125-1129.

T

Thompson, A (2025) Analytical results for combined data and model uncertainty for machine learning regression. Measurement: Sensors, 38. 101788

V

Videla, A; Lines, K (2025) Functional Programming (with some Type Theory) for Metrology. NPL Report. MS 60