6 research outputs found
Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer
Background: Immunohistochemistry (IHC) is often used in personalisation of cancer treatments. Analysis of large data sets to uncover predictive biomarkers by specialists can be enormously time-consuming. Here we investigated crowdsourcing as a means of reliably analysing immunostained cancer samples to discover biomarkers predictive of cancer survival.
Methods: We crowdsourced the analysis of bladder cancer TMA core samples through the smartphone app âReverse the Oddsâ. Scores from members of the public were pooled and compared to a gold standard set scored by appropriate specialists. We also used crowdsourced scores to assess associations with disease-specific survival.
Results: Data were collected over 721 days, with 4,744,339 classifications performed. The average time per classification was approximately 15âs, with approximately 20,000âh total non-gaming time contributed. The correlation between crowdsourced and expert H-scores (staining intensityâĂâproportion) varied from 0.65 to 0.92 across the markers tested, with six of 10 correlation coefficients at least 0.80. At least two markers (MRE11 and CK20) were significantly associated with survival in patients with bladder cancer, and a further three markers showed results warranting expert follow-up.
Conclusions: Crowdsourcing through a smartphone app has the potential to accurately screen IHC data and greatly increase the speed of biomarker discovery
Assessing length of stay and associated characteristics of geriatric patients in Northern Ireland
Utilization Patterns of Glucagon-Like Peptide-1 Receptor Agonists in Patients with Type 2 Diabetes Mellitus in Italy: A Retrospective Cohort Study
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Research data supporting "Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer"
Complete data set for the manuscript "Crowdsourcing the general public for large scale molecular pathology studies in cancer". Published at: http://dx.doi.org/10.1016/j.ebiom.2015.05.009This work was supported by the Cancer Research UK [C490/A10124, C490/A16561