Innovative new medicines used in conjunction with neoadjuvant chemotherapy (NACT) may lead to a higher pathological complete response (pCR), and therefore a better chance of survival for patients diagnosed with eTNBC cancer. The Edinburgh Cancer Informatics, in partnership with DATA-CAN, ran a retrospective, longitudinal cohort study using routinely collected data to better describe differences in […]
Collaboration with the Edinburgh Cancer Informatics team enabled an investigation of the Real-World Impact of stereotactic ablative body radiotherapy (SABR) along with other conventional methods (conventional radiotherapy and surgery) on Stage I Non-Small-Cell Lung Cancer (NSCLC) patients in South-East Scotland. A total of 1143 patients discussed at MDM between January 2012 and December 2019 were selected for this study from the Edinburgh Cancer Centre Lung […]
Summary by Dr Iain Phillips. The Edinburgh Cancer Informatics is supporting a prehabilitation project at St John’s hospital, Livingston, West Lothian for patients with likely lung cancer. All patients with stage 3 and 4 radiologically diagnosed lung cancer are offered prehabilitation. This involves a thorough pre visit assessment. All patients are seen by a Consultant […]
In an effort to better describe patients affected with node-positive HR+, HER2− early breast cancer, the Edinburgh Cancer Informatics conducted a retrospective study looking at the demographic and clinical characteristics of these patients in South-East Scotland, in a real-world setting. Long term outcomes and treatment profiles were also reported, along with healthcare utilisation. Such audits are […]
Brain Tumour Pathway – a REDCap Project Critical to accelerating the discovery of new therapies for brain tumours and their translation into the clinic, is to investigate diagnosis, treatment and outcomes at a population level, mapping this to molecular interrogation of resected tumour tissue, and liquid biopsies from patients. In collaboration with researchers at […]
…Our new R package! Methods developed in social network science have been successfully applied in the biomedical domain over for the past two decades. Examples include splitting biological networks into communities, to discover highly enriched complexes with specific diseases and functions. We developed the Bioconductor package BioNAR to provide biomedical researchers with a network analysis […]
This Data Linkage study exploits historically strong maternity and cancer registration data in Scotland to produce more evidence to help women in their decision making on pregnancy after treatment for early breast cancer. The impact of childbirth on survival after breast cancer remains controversial. National cancer and birth data were used to analyse an unbiased […]
More information about the position here.
We have an exciting PhD studentship opportunity starting September 2022, please use the link below for additional information: A multimodal deep learning model to predict individual cancer patient survival probabilities Closing date for applications is 27 May 2022. Feel free to share if you know anyone who would be interested!
More details here: https://apply.jobs.scot.nhs.uk/displayjob.aspx?jobid=84166