A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data

arXiv:2403.05606v1 Announce Type: new
Abstract: Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning offers a promising solution, while the development of such technologies is hindered by the scarcity of data on rare conditions and the demand for models that are both interpretable and trustworthy in a clinical context. Interpretable AI, with its capacity for human-readable outputs, can facilitate validation by clinicians and contribute to medical …

abstract arxiv challenge clinical concept cs.ai cs.cl cs.cv cs.lg data development diagnosis diseases expertise identification machine machine learning multimodal multimodal data practice rare diseases solution technologies type