Gwen Saalmink

BSc (Hons) Adult Nursing (2017), MSc International Politics (2010), BA English (2009)

PhD Student

Phone: 0113 2067500
Email: G.B.A.Saalmink@leeds.ac.uk

Gwen was awarded an NIHR Clinical Doctoral Research Fellowship in 2024 to undertake her PhD which she is completing part time whilst continuing to work as senior research nurse in Oncology. Her research project is looking at developing a 21st century model of nurse-led follow-up after curative germ cell tumour treatment.

She has worked as an Oncology nurse since 2017 and previously worked with the Patient Reported Outcomes Group as a research nurse between 2020 and 2022.

Research Interests

Gwen’s main interests lie in patient reported outcomes, telemedicine, digital health and oncology.

Presentations and Publications

  • Saalmink G & Iles-Smith H 2020. Could survivor’s guilt be a lasting impact for patients recovering from COVID-19? Cancer Nursing Practice 19 (5). Pp 12-13. doi: 10.7748/cnp.19.5.12.s9
  • Laios, A.; De Freitas, D.L.D.; Saalmink, G.; Tan, Y.S.; Johnson, R.; Zubayraeva, A.; Munot,S.; Hutson, R.; Thangavelu, A.; Broadhead, T.; et al. Stratification of Length of Stay Prediction following Surgical Cytoreduction in Advanced High-Grade Serous Ovarian Cancer Patients Using Artificial Intelligence; the Leeds L-AI-OS Score. Curr. Oncol. 2022, 29, 9088–9104.
  • Laios, A.; De Oliveira Silva, R.V.; Dantas De Freitas, D.L.; Tan, Y.S.; Saalmink, G.; Zubayraeva, A.; Johnson, R.; Kaufmann, A.; Otify, M.; Hutson, R.; et al. Machine Learning-Based Risk Prediction of Critical Care Unit Admission for Advanced Stage High Grade Serous Ovarian Cancer Patients Undergoing Cytoreductive Surgery: The Leeds-Natal Score. J. Clin. Med. 2022, 11, 87.
  • Laios A, Vanessa De Oliveira R, Lucas D , Tan Y, Saalmink G, Zubayraeva A, Hutson R,  Thangavelu A, Broadhead T, Nugent D, Theophilou G, Lima K , DeJong D. 2021. Machine Learning outperforms logistic regression in predicting accuracy of CCU admission for high grade serous advanced ovarian cancer patients. International Journal of Gynecological Cancer 31 (Suppl 3): A179.1-A179. DOI: 10.1136/ijgc-2021-ESGO.304
  • Alexandros Laios, Camilo De Lelis Medeiros-de-Morais, Yong Tan, Gwendolyn Saalmink, Mohamed Otify, Amudha Thangavelu, Richard Hutson, David Nugent, Kassio Michell Gomes de Lima, George Theophilou. 2020. Testing prediction accuracy of ideal and prolonged length of hospital stay following ovarian cancer cytoreduction using machine learning methods. International Journal of Gynecological Cancer 30 (Suppl 4). DOI: 10.1136/ijgc-2020-ESGO.194