Imperial College London

Dr. Alexander R.M. Lyons, Ph.D

Faculty of MedicineSchool of Public Health

Research Associate/Project Manager



+44 (0)20 7594 2771a.lyons




Reynolds BuildingCharing Cross Campus





Publication Type

5 results found

Stevens C, Lyons A, Dharmayat K, Mahani A, Ray K, Vallejo-Vaz AJ, Taghavi Azar Sharabiani Met al., 2023, Ensemble machine learning methods in screening electronic health records: a scoping review, Digital Health, Vol: 9, Pages: 1-17, ISSN: 2055-2076

Background:Electronic Health Records (EHRs) provide the opportunity to identify undiagnosed individuals likely to have a given disease using Machine Learning (ML) techniques, and who could then benefit from more medical screening and case finding, reducing the number needed to screen with convenience and healthcare cost savings. Ensemble Machine Learning Models (EMLs) combining multiple prediction estimates into one, are often said to provide better predictive performances than non-ensemble models. Yet, to our knowledge, no literature review summarises the use and performances of different types of EMLs in the context of medical pre-screening. Method:We aimed to conduct a scoping review of the literature reporting the derivation of EMLs for screening of EHRs. We searched EMBASE and MEDLINE databases across all years applying a formal search strategy using terms related to medical screening, EHR and ML. Data were collected, analysed, and reported in accordance with the PRISMA scoping review guideline. Results:A total of 3,355 articles were retrieved, of which 145 articles met our inclusion criteria and were included in this study. EMLs were increasingly employed across several medical specialities and often outperformed non-ensemble approaches. EMLs with complex combination strategies and heterogeneous classifiers often outperformed other types of EMLs but were also less used. EML methodologies, processing steps and data sources were often not clearly described. Conclusions:Our work highlights the importance of deriving and comparing the performances of different types of EMLs when screening EHRs and underscores the need for more comprehensive reporting of ML methodologies employed in clinical research.

Journal article

Vallejo-Vaz A, Stevens C, Dharmayat K, Lyons A, Brandts J, Freiberger T, Hovingh GK, Kastelein JJ, Mata P, Raal FJ, Santos R, Soran H, Watts GF, Catapano AL, Ray Ket al., 2022, Identification, characteristics and management of adults with heterozygous Familial Hypercholesterolaemia in high and non-high income countries participating in the EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC), European Atherosclerosis Society Congress 2022, Publisher: Elsevier, Pages: 15-16, ISSN: 0021-9150

Conference paper

Vallejo-Vaz AJ, Stevens CAT, Lyons ARM, Dharmayat KI, Freiberger T, Hovingh GK, Mata P, Raal FJ, Santos RD, Soran H, Watts GF, Abifadel M, Aguilar-Salinas CA, Alhabib KF, Alkhnifsawi M, Almahmeed W, Alnouri F, Alonso R, Al-Rasadi K, Al-Sarraf A, Al-Sayed N, Araujo F, Ashavaid TF, Banach M, Béliard S, Benn M, Binder CJ, Bogsrud MP, Bourbon M, Chlebus K, Corral P, Davletov K, Descamps OS, Durst R, Ezhov M, Gaita D, Genest J, Groselj U, Harada-Shiba M, Holven KB, Kayikcioglu M, Khovidhunkit W, Lalic K, Latkovskis G, Laufs U, Liberopoulos E, Lima-Martinez MM, Lin J, Maher V, Marais AD, März W, Mirrakhimov E, Miserez AR, Mitchenko O, Nawawi H, Nordestgaard BG, Panayiotou AG, Paragh G, Petrulioniene Z, Pojskic B, Postadzhiyan A, Raslova K, Reda A, Reiner Ž, Sadiq F, Sadoh WE, Schunkert H, Shek AB, Stoll M, Stroes E, Su T-C, Subramaniam T, Susekov AV, Tilney M, Tomlinson B, Truong TH, Tselepis AD, Tybjæg-Hansen A, Vázquez Cárdenas A, Viigimaa M, Wang L, Yamashita S, Tokgozoglu L, Catapano AL, Ray KK, Kastelein JJP, Bruckert E, Vohnout B, Schreier L, Pang J, Ebenbichler C, Dieplinger H, Innerhofer R, Winhofer-Stöckl Y, Greber-Platzer S, Krychtiuk K, Speidl W, Toplak H, Widhalm K, Stulnig T, Huber K, Höllerl F, Rega-Kaun G, Kleemann L, Mäser M, Scholl-Bürgi S, Säly C, Mayer FJ, Sablon G, Tarantino E, Nzeyimana C, Pojskic L, Sisic I, Nalbantic AD, Jannes CE, Pereira AC, Krieger JE, Petrov I, Goudev A, Nikolov F, Tisheva S, Yotov Y, Tzvetkov I, Baass A, Bergeron J, Bernard S, Brisson D, Brunham LR, Cermakova L, Couture P, Francis GA, Gaudet D, Hegele RA, Khoury E, Mancini GBJ, McCrindle BW, Paquette M, Ruel I, Cuevas A, Asenjo S, Wang X, Meng K, Song X, Yong Q, Jiang T, Liu Z, Duan Y, Hong J, Ye P, Chen Y, Qi J, Liu Z, Li Y, Zhang C, Peng J, Yang Y, Yu W, Wang Q, Yuan H, Cheng S, Jiang L, Chong M, Jiao J, Wu Y, Wen W, Xu L, Zhang R, Qu Y, He J, Fan X, Wang Z, Chow E, Pećin I, Perica D, Symeonides P, Vrablik M, Ceska R, Soska V, Tichy L, Adamkova V, Franekova J, Cifkova R, Kramet al., 2021, Global perspective of familial hypercholesterolaemia: a cross-sectional study from the EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC), The Lancet, Vol: 398, Pages: 1713-1725, ISSN: 0140-6736

BackgroundThe European Atherosclerosis Society Familial Hypercholesterolaemia Studies Collaboration (FHSC) global registry provides a platform for the global surveillance of familial hypercholesterolaemia through harmonisation and pooling of multinational data. In this study, we aimed to characterise the adult population with heterozygous familial hypercholesterolaemia and described how it is detected and managed globally.MethodsUsing FHSC global registry data, we did a cross-sectional assessment of adults (aged 18 years or older) with a clinical or genetic diagnosis of probable or definite heterozygous familial hypercholesterolaemia at the time they were entered into the registries. Data were assessed overall and by WHO regions, sex, and index versus non-index cases.FindingsOf the 61 612 individuals in the registry, 42 167 adults (21 999 [53·6%] women) from 56 countries were included in the study. Of these, 31 798 (75·4%) were diagnosed with the Dutch Lipid Clinic Network criteria, and 35 490 (84·2%) were from the WHO region of Europe. Median age of participants at entry in the registry was 46·2 years (IQR 34·3–58·0); median age at diagnosis of familial hypercholesterolaemia was 44·4 years (32·5–56·5), with 40·2% of participants younger than 40 years when diagnosed. Prevalence of cardiovascular risk factors increased progressively with age and varied by WHO region. Prevalence of coronary disease was 17·4% (2·1% for stroke and 5·2% for peripheral artery disease), increasing with concentrations of untreated LDL cholesterol, and was about two times lower in women than in men. Among patients receiving lipid-lowering medications, 16 803 (81·1%) were receiving statins and 3691 (21·2%) were on combination therapy, with greater use of more potent lipid-lowering medication in men than in women. Median LDL cholesterol

Journal article

Vallejo-Vaz AJ, Dharmayat K, Stevens C, Lyons A, Brandts J, Catapano AL, Freiberger T, Hovingh K, Kastelein JJ, Mata P, Raal FJ, Santos RD, Soran H, Watts GF, Ray KKet al., 2020, Characteristics of adults with heterozygous familial hypercholesterolaemia stratified by gender: preliminary analysis from the eas fhsc global registry on over 36,000 cases of familial hypercholesterolaemia, European Atherosclerosis Society Congress, Publisher: Elsevier, Pages: e13-e13, ISSN: 0021-9150

Conference paper

Dharmayat K, Stevens C, Lyons A, Catapano AL, Freiberger T, Hovingh K, Kastelein JJ, Mata P, Raal FJ, Santos RD, Soran H, Watts GF, Ray KK, Vallejo-Vaz AJet al., 2020, Heterozygous familial hypercholesterolaemia in children: preliminary analysis from the eas fhsc global registry on over 7,900 children with familial hypercholesterolaemia, European Atherosclerosis Society Congress, Publisher: Elsevier, Pages: e76-e76, ISSN: 0021-9150

Conference paper

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