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Health care professionals’ perceptions of machine learning based clinical decision support systems for oesophageal cancer management

Authors: Catherine Webb,Navamayooran Thavanesan,Mohammad Naiseh,Rachel Dewar-Haggart,Tim Underwood,Ganesh Vigneswaran
Journal: Computers in Biology and Medicine
Publisher: Elsevier BV
Publish date: 2026-1
ISSN: 0010-4825 DOI: 10.1016/j.compbiomed.2025.111373
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– Table 3 rank comparison is not valid as presented. The ML ranking includes variables never offered in the survey (“Epoch”, “Referring location”), and “Comorbidities (summed)” adds permutation importances of separate CCI variables, which is not appropriate for correlated features. Please re-rank the ML model using only survey-available factors and clarify how CCI importances were aggregated.
– The gender conclusion is overstated. Fig. 4 gives gender only **1.13%** relative importance—lower than several survey-ranked factors and only marginally above CVD—yet the text says gender had greater influence in the model than its conscious importance would support. Also CHF is 0.15% in Fig. 4 but 0.2% in the text.
– Table 6 is internally inconsistent: one row has no theme label (presumably “Transparency and Safeguarding”), and “Inquire requirements” appears to be a typo for “Input requirements.” Table 4 is also duplicated, with the first version garbled.
– The “generally positive” conclusion is based on 33/60 respondents for likelihood and 22/60 for barriers. Given attrition and self-selection, how did you handle missingness, and do the abstract/conclusion claims exceed what these denominators support?

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