Isaiah Gitonga, Deirdre Desmond, Rebecca Maguire
Who uses connected health technologies after a cancer diagnosis? evidence from the US Health Information National Trends Survey
Journal of cancer survivorship : research and practice
mapping metabolitespecific data pathways within cellular metabolism major data analysis step needed biochemical interpretation variety machine learning approaches particularly deep learning approaches used predict metabolitetopathway mappings utilizing training dataset known metabolitetopathway mappings training datasets derived kyoto encyclopedia genes genomes kegg however several prior published machine learning approaches utilized erroneous keggderived training dataset used smiles molecular representations strings keggsmiles dataset contained sizable proportion 26 duplicate entries presence many duplicates taint training testing sets generated kfold crossvalidation keggsmiles dataset therefore kfold crossvalidation performance resulting machine learning models grossly inflated erroneous presence duplicate entries describe evaluate keggsmiles dataset others may avoid using also identify prior publications utilized erroneous keggsmiles dataset machine learning results properly critically evaluated addition demonstrate reduction model kfold crossvalidation cv performance deduplicating keggsmiles dataset cautionary tale properly vetting prior published benchmark datasets using machine learning approaches hope others avoid similar mistakes