Patient-Oriented Questionnaires and Machine Learning for Rare Disease Diagnosis: A Systematic Review.

ABSTRACT: Background: A major challenge faced by patients with rare diseases (RDs) often stems from delays in diagnosis, typically due to nonspecific clinical symptoms or doctors' limited experience in connecting symptoms to the underlying RD. Using patient-oriented questionnaires (POQs) as a data source for machine learning (ML) techniques can serve as a potential solution. These questionnaires enable patients to portray their day-to-day experiences living with their condition, irrespective of clinical symptoms. This systematic review-registered at PROSPERO with the Registration-ID: CRD42023490838-aims to present the current state of research in this domain by conducting a systematic literature search and identifying the potentials and limitations of this methodology. Methods: The rev

SUBMITTER: Brauner LE 

PROVIDER: S-EPMC11396573 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature