James Liley

1.1k total citations
10 papers, 122 citations indexed

About

James Liley is a scholar working on Genetics, Pulmonary and Respiratory Medicine and Health Informatics. According to data from OpenAlex, James Liley has authored 10 papers receiving a total of 122 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Genetics, 2 papers in Pulmonary and Respiratory Medicine and 2 papers in Health Informatics. Recurrent topics in James Liley's work include Genetic Associations and Epidemiology (3 papers), Diabetes and associated disorders (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). James Liley is often cited by papers focused on Genetic Associations and Epidemiology (3 papers), Diabetes and associated disorders (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). James Liley collaborates with scholars based in United Kingdom, Germany and United States. James Liley's co-authors include Chris Wallace, Bilal A. Mateen, Alastair K. Denniston, Chris Holmes, Sebastian J. Vollmer, John A. Todd, Marc P. van der Schee, Jan O. Cowan, Rochelle Palmay and D. Robin Taylor and has published in prestigious journals such as Nature Genetics, European Respiratory Journal and PLoS Genetics.

In The Last Decade

James Liley

9 papers receiving 122 citations

Peers

James Liley

GENET

MB

EPIDE

SURGE

RNMI

Matthew Page United Kingdom

Aayushee Jain United States

Bennet Peterson United States

Robbert Struyven United Kingdom

Reeta Metta United States

Silvia Müller-Hagedorn Germany

Markus Leber Germany

Mutali Musa Nigeria

Aleena Notary United States

E. Mazzeo Italy

Matthew Page United Kingdom

James Liley

20 ×0.4

GENET

50 ×1.7

MB

20 ×1.3

EPIDE

14 ×1.0

SURGE

6 ×0.4

RNMI

Citations per year, relative to James Liley James Liley (= 1×) peers Matthew Page

Countries citing papers authored by James Liley

Since Specialization

Citations

This map shows the geographic impact of James Liley's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by James Liley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Liley more than expected).

Fields of papers citing papers by James Liley

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Liley. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by James Liley. The network helps show where James Liley may publish in the future.

Co-authorship network of co-authors of James Liley

This figure shows the co-authorship network connecting the top 25 collaborators of James Liley. A scholar is included among the top collaborators of James Liley based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James Liley. James Liley is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Dudley, Robert, Guy Dodgson, Emmanuel Ogundimu, et al.. (2024). Effects of a novel, brief psychological therapy (Managing Unusual Sensory Experiences) for hallucinations in first episode psychosis (MUSE FEP): Findings from an exploratory randomised controlled trial. Journal of Psychiatric Research. 174. 289–296. 3 indexed citations

2.

Liley, James, Gergő Bohner, Bilal A. Mateen, et al.. (2024). Development and assessment of a machine learning tool for predicting emergency admission in Scotland. npj Digital Medicine. 7(1). 277–277. 1 indexed citations

3.

Aslett, Louis J. M., et al.. (2024). Ethical considerations of use of hold-out sets in clinical prediction model management. AI and Ethics. 5(3). 2435–2444. 1 indexed citations

4.

Liley, James, Katherine Bunclark, Michael Newnham, et al.. (2024). Development of an open-source tool for risk assessment in pulmonary endarterectomy. European Respiratory Journal. 65(3). 2401001–2401001.

5.

Bunclark, Katherine, James Liley, Alessandro Ruggiero, et al.. (2023). An open-source tool for risk prediction in operable CTEPH. PA5191–PA5191. 1 indexed citations

6.

Liley, James & Chris Wallace. (2021). Accurate error control in high‐dimensional association testing using conditional false discovery rates. Biometrical Journal. 63(5). 1096–1130. 6 indexed citations

7.

Mateen, Bilal A., James Liley, Alastair K. Denniston, Chris Holmes, & Sebastian J. Vollmer. (2020). Improving the quality of machine learning in health applications and clinical research. Nature Machine Intelligence. 2(10). 554–556. 43 indexed citations

8.

Liley, James, John A. Todd, & Chris Wallace. (2016). A method for identifying genetic heterogeneity within phenotypically defined disease subgroups. Nature Genetics. 49(2). 310–316. 16 indexed citations

9.

Liley, James & Chris Wallace. (2015). A Pleiotropy-Informed Bayesian False Discovery Rate Adapted to a Shared Control Design Finds New Disease Associations From GWAS Summary Statistics. PLoS Genetics. 11(2). e1004926–e1004926. 48 indexed citations

10.

Schee, Marc P. van der, James Liley, Rochelle Palmay, Jan O. Cowan, & D. Robin Taylor. (2012). Predicting Steroid Responsiveness In Patients With Asthma Using The Electronic Nose. A3946–A3946. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact