Giuseppe Minervini, Ludovica Nucci, Maria Rosaria Barillari, Rossana Patricia Rotolo, Vincenzo Grassia, Fabrizia d'Apuzzo
Evaluation of tinnitus in patients with Temporomandibular Disorders through Axis II of the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) and the Tinnitus Handicap Inventory (THI)
Journal of oral rehabilitation
detailed invasive clinical investigations required identify causes haematuria highly unbalanced patient population predominantly male wide range potential causes make ability correctly classify patients identify patientspecific biomarkers major challenge studies shown possible improve diagnosis using multimarker analysis even unbalanced datasets applying advanced analytical methods applied several machine learning algorithms classify patients haematuria patient cohort habio analysing multiple biomarkers identify relevant ones applied several classification feature selection methods kmeans clustering decision trees random forest lime explainer cactus algorithm stratify patients two groups healthy clear cause haematuria sick identified cause haematuria eg bladder cancer infection classification performance models compared biomarkers identified important algorithms also analysed relation involvement pathological processes results showed high unbalance datasets significantly affected classification random forest decision trees leading overestimation sick class low model performance cactus algorithm robust unbalance dataset cactus obtained balanced accuracy 0747 genders 0718 females 0803 males analysis showed classification process whole dataset microalbumin male gender tpsa emerged informative biomarkers males age microalbumin tpsa cystatin c bta s100a4 significant biomarkers females microalbumin il8 perk cxcl16 cactus algorithm demonstrated improved performance compared methods decision trees random forest additionally identified relevant biomarkers specific patient group could considered future novel biomarkers diagnosis results potential inform future research provide new personalised diagnostic approaches tailored directly needs individuals