Jones, Angus G.

The majority of patients with long-duration type 1 diabetes are insulin microsecretors and have functioning beta cells

Oram, R. A., Jones, A. G., Besser, R. E. J., Knight, B. A., Shields, B. M., Brown, R. J., Hattersley, A. T., & McDonald, T. J. (2014) · Diabetologia

Diabetes and associated disordersPancreatic function and diabetes

Cited by 298

Type 1 diabetes defined by severe insulin deficiency occurs after 30 years of age and is commonly treated as type 2 diabetes

Thomas, N. J., Lynam, A. L., Hill, A. V., Weedon, M. N., Shields, B. M., Oram, R. A., McDonald, T. J., Hattersley, A. T., & Jones, A. G. (2019) · Diabetologia

Diabetes and associated disordersDiabetes Management and Research

Cited by 183

Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

Lynam, A. L., Dennis, J. M., Owen, K. R., Oram, R. A., Jones, A. G., Shields, B. M., & Ferrat, L. A. (2020) · Diagnostic and Prognostic Research

Artificial Intelligence in HealthcareStatistical Methods in Epidemiology

Cited by 142

Can clinical features be used to differentiate type 1 from type 2 diabetes? A systematic review of the literature

Shields, B. M., Peters, J. L., Cooper, C., Lowe, J., Knight, B. A., Powell, R. J., Jones, A., Hyde, C. J., & Hattersley, A. T. (2015) · BMJ Open

Diabetes and associated disordersDiabetes Management and Research

Cited by 126

Latent autoimmune diabetes of adults (LADA) is likely to represent a mixed population of autoimmune (type 1) and nonautoimmune (type 2) diabetes

Jones, A. G., McDonald, T. J., Shields, B. M., Hagopian, W., & Hattersley, A. T. (2021) · Diabetes Care

Diabetes and associated disordersDiabetes Management and Research

Cited by 122

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

Allesøe, R. L., Lundgaard, A. T., Hernández Medina, R., Aguayo-Orozco, A., Johansen, J., Nissen, J. N., Brorsson, C., Mazzoni, G., Niu, L., Biel, J. H., et al. (2023) · Nature Biotechnology

Bioinformatics and Genomic NetworksComputational Drug Discovery Methods

Cited by 111

Predicting and elucidating the etiology of fatty liver disease: a machine learning modeling and validation study in the IMI DIRECT cohorts

Atabaki-Pasdar, N., Ohlsson, M., Viñuela, A., Frau, F., Pomares-Millan, H., Haid, M., Jones, A. G., Thomas, E. L., Koivula, R. W., Kurbasic, A., et al. (2020) · PLOS Medicine

Liver Disease Diagnosis and TreatmentAlcohol Consumption and Health Effects

Cited by 97

Practical classification guidelines for diabetes in patients treated with insulin: a cross-sectional study of the accuracy of diabetes diagnosis

Hope, S. V., Wienand-Barnett, S., Shepherd, M., King, S. M., Fox, C., Khunti, K., Oram, R. A., Knight, B. A., Hattersley, A. T., Jones, A. G., et al. (2016) · British Journal of General Practice

Diabetes and associated disordersDiabetes Management and Research

Cited by 87

Urine C-peptide creatinine ratio is a noninvasive alternative to the mixed-meal tolerance test in children and adults with type 1 diabetes

Besser, R. E. J., Ludvigsson, J., Jones, A. G., McDonald, T. J., Shields, B. M., Knight, B. A., & Hattersley, A. T. (2011) · Diabetes Care

Diabetes and associated disordersPancreatic function and diabetes

Cited by 82

Development and validation of multivariable clinical diagnostic models to identify type 1 diabetes requiring rapid insulin therapy in adults aged 18-50 years

Lynam, A., McDonald, T., Hill, A., Dennis, J., Oram, R., Pearson, E., Weedon, M., Hattersley, A., Owen, K., Shields, B., et al. (2019) · BMJ Open

Diabetes and associated disordersDiabetes Management and Research

Cited by 72

Random non‐fasting C–peptide: bringing robust assessment of endogenous insulin secretion to the clinic

Hope, S. V., Knight, B. A., Shields, B. M., Hattersley, A. T., McDonald, T. J., & Jones, A. G. (2016) · Diabetic Medicine

Diabetes Management and ResearchPancreatic function and diabetes

Cited by 68

Effective interventions in preventing gestational diabetes mellitus: A systematic review and meta-analysis

Takele, W. W., Vesco, K. K., Josefson, J., Redman, L. M., Hannah, W., Bonham, M. P., Chen, M., Chivers, S. C., Fawcett, A. J., Grieger, J. A., et al. (2024) · Communications Medicine

Gestational Diabetes Research and ManagementDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 55

The challenges of identifying and studying type 1 diabetes in adults

Thomas, N. J., & Jones, A. G. (2023) · Diabetologia

Diabetes and associated disordersDiabetes Management and Research

Cited by 54