Minne Fekkes, Frans I M Pijpers, A Miranda Fredriks, Ton Vogels, S Pauline Verloove-Vanhorick
Do bullied children get ill, or do ill children get bullied? A prospective cohort study on the relationship between bullying and health-related symptoms
Pediatrics
current medical standard setting oral cancer oc diagnosis histological examination tissue sample taken oral cavity process timeconsuming invasive alternative approach acquiring brush sample followed cytological analysis using microscope skilled cytotechnologists able detect changes due malignancy however introducing approach clinical routine associated challenges lack resources experts design trustworthy oc detection system assist cytotechnologists interested deep learning based methods reliably detect cancer given perpatient labels thereby minimizing annotation bias also provide information regarding cells relevant diagnosis thereby enabling supervision understanding study perform comparison two approaches suitable oc detection interpretation conventional single instance learning sil approach ii modern multiple instance learning mil method facilitate systematic evaluation considered approaches addition real oc dataset patientlevel ground truth annotations also introduce synthetic datasetpapqmnist dataset shares several properties oc data image size large varied number instances per bag may therefore act proxy model real oc dataset contrast oc data offers reliable perinstance ground truth defined design papqmnist additional advantage visually interpretable nonexperts simplifies analysis behavior methods oc papqmnist data evaluate performance methods utilizing three different neural network architectures study indicates somewhat surprisingly synthetic real data performance sil approach better equal performance mil approach visual examination cytotechnologist indicates methods manage identify cells deviate normality including malignant cells well suspicious dysplasia share code open source