Noah van Dongen, Jan Sprenger, Eric-Jan Wagenmakers
A Bayesian perspective on severity: risky predictions and specific hypotheses
Psychonomic bulletin & review
medical images contain various abnormal regions closely related lesions diseases abnormality lesion one major concerns clinical practice therefore becomes key answering questions medical images however recent efforts still focus constructing generic visual question answering framework medicaldomain tasks adequate practical medical requirements applications paper present two novel medicalspecific modules named multiplication anomaly sensitive module residual anomaly sensitive module utilize weakly supervised anomaly localization information medical visual question answering firstly proposed multiplication anomaly sensitive module designed anomalyrelated questions mask feature whole image according anomaly location map secondly residual anomaly sensitive module could learn flexible anomaly feature preserving information original questioned image helpful answering anomalyunrelated questions thirdly transformer decoder multitask learning strategy combined enhance questionreasoning ability model generalization performance finally qualitative quantitative experiments variety medical datasets exhibit superiority proposed approaches compared stateoftheart methods