A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data
2023 · BMC Bioinformatics · 62 citations
https://doi.org/10.1186/s12859-023-05262-8
O
Oskar Wysocki
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Oskar Wysocki is an academic researcher from Cancer Research UK Manchester Institute. The author has contributed to research in topics: Biomedical Text Mining and Ontologies & Vehicle emissions and performance & Engine and Fuel Emissions. The author has an h-index of 9, co-authored 46 publications.
ORCID: 0000-0002-7053-4919Papers by this author
worksLongitudinal characterisation of haematological and biochemical parameters in cancer patients prior to and during COVID-19 reveals features associated with outcome
2021 · ESMO Open · 21 citations
https://doi.org/10.1016/j.esmoop.2020.100005
Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation
2024 · Journal of Biomedical Informatics · 6 citations
https://doi.org/10.1016/j.jbi.2024.104724
An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves
2022 · Cancers · 2 citations
https://doi.org/10.3390/cancers14163931
1769eP Patient perceptions of artificial intelligence-assisted eye imaging: Insights from the A-EYE study
2025 · Annals of Oncology · 0 citations
https://doi.org/10.1016/j.annonc.2025.08.2398
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