Author

Konstantinos Balaskas

Moorfields Eye Hospital NHS Foundation TrustORCID 0000-0002-7690-6277Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:benchmarking· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Robyn H. GuymeriD· 2 shared A. J. McKnight· 1 shared Aaron LeeiD· 1 shared Adnan TufailiD· 1 shared Adrian Bateman· 1 shared Ahmed Iqbal· 1 shared Ajoy BardhaniD· 1 shared Alastair Keith DennistoniD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Robyn H. GuymerORCID

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Author profile →

3 papers

Recent·Most cited

Genetic Risk of Reticular Pseudodrusen in Age-Related Macular Degeneration: HTRA1/lncRNA BX842242.1 dominates, with no evidence for Complement Cascade involvement

Samaneh Farashi, Carla J. Abbott, Brendan R. E. Ansell, Zhichao Wu, Lebriz Altay, Ella Arnon, Louis Arnould, Yelena Bagdasarova, Konstantinos Balaskas, Fred Kuanfu Chen, Emily Y. Chew, Itay Chowers, Steven Clarke, Catherine A. Cukras, Cécile Delcourt, , Melanie Bahlo

Nature Communications · Dec 8, 2025Peer-reviewedGenetic & Genomic Medicine

Defining an Ageing-Related Pathology, Disease or Syndrome: International Consensus Statement

Emma L. Short, ICCARP, Ian Michael Adcock, Bilal Al-Sarireh, Ann Ager, Ramzi Ajjan, Naveed Akbar, Michael A. Akeroyd, Ghada Alsaleh, Ghada Al-Sharbatee, Kambiz N. Alavian, Winfried Amoaku, Julie Andersen, Chrystalina A. Antoniades, Mark J. Arends, , Werner Kempf

The paper establishes international consensus criteria to classify ageing-related pathologies, diseases, and syndromes based on age progression, functional decline, and human evidence.

GeroScience · Sep 21, 2024Peer-reviewedGenetic & Genomic Medicine

Feasibility of Automated Deep Learning Design for Medical Image Classification by Healthcare Professionals with Limited Coding Experience

Livia Faes, Siegfried K. Wagner, Dun Jack Fu, Xiaoxuan Liu, Edward Korot, Joseph R. Ledsam, Trevor Back, Reena Chopra, Nikolas Pontikos, Christoph Kern, Gabriella Moraes, Martin K. Schmid, Dawn A. Sim, Konstantinos Balaskas, Lucas M. Bachmann, , Pearse Andrew Keane

This study evaluates automated deep learning tools for medical image classification by non-experts, showing high performance in some tasks but limitations in external validation and dataset quality.

bioRxiv · May 27, 2019 · PreprintBioinformatics