A novel online training platform for medical image interpretation

Abstract

One of the major problems in the health area is false positive and negative diagnoses, especially in the interpretation of radiological images. Several papers affirm that the radiologist experience helps in accurate diagnosis, reducing inter-observer and intra-observer variability. We assume that the lack of training is causing this problem and if a good training process is on place can reduce the level of false positive and false negative diagnosis, and this training should start at the undergraduate level. Thus, this paper aims to show an online training platform applied to of interpretation imaging learning. The platform was developed using the php language and is hosted on the 000webhost server, consisting of an image base (format, png, jpg, tiff and DICOM), diagnostic imaging tests and user training quiz (students/residents) about radiographic images interpretation. The teacher can add images, prepare diagnostic tests and create questionnaires. The users perform the diagnostic tests and answer the questionnaires, obtaining a score in real time. This platform can be used inside and outside the classroom, where they can train the diagnosis by image to improve their knowledge. The platform was tested by 20 medical students that, after use it, answered the usability tests based on the SUS scale. The usability tests results showed that 90 of the users gave the maximum concept to the platform.