Construction of A Multimodal Digital Assessment Model for Myasthenia Gravis

The goal is to define the multimodal digital phenotypes of myasthenia gravis patients, determine the specificities of their symptoms, and develop a digital evaluation model and remote assessment system that is objective, precise, and user-friendly. This will provide a scientific foundation and technical support for diagnosing, treating, and rehabilitating individuals with MG.

Key issues to be addressed include:

• Whether digital phenotyping can comprehensively represent the disease characteristics and severity gradations in MG.
• The feasibility of using multimodal digital phenotypic modeling for the objective evaluation of MG.
• The challenges and obstacles faced by the AI-enhanced medical model in clinical demonstration applications.

The study is focused on three main objectives:

• Perform a descriptive analysis and comparison of phenotypic data across various subgroups to pinpoint key characteristics associated with MG disease grade and scale score.
• Construct a digital evaluation model for MG patients using chosen features, validate the model with prospectively gathered data, and conduct a correlative analysis with the clinical functional scales to assess its effectiveness on predicting MG symptom grading and disease progression.
• Develop a patient-centric remote evaluation system utilizing the refined MG digital evaluation model to facilitate its application in real-world clinical settings.

Inclusion criteria

For Patients with MG

• Patients have a confirmed diagnosis of myasthenia gravis and be over 18 years old.
• Patients have the clinical classification of Myasthenia Gravis Foundation of America (MGFA) within I-IV, or be asymptomatic after treatment.
• Patients must sign the informed consent form and the privacy confidentiality agreement.

For Healthy Participants

• Age group matched with MG participants

Exclusion criteria

For Patients with MG

• Patients are in the crisis stage of myasthenia gravis (MGFA class V) and unable to cooperate with scoring.
• Patients are with severe cardiopulmonary diseases and unable to cooperate with the scoring.
• Patients with any psychiatric disorder or cognitive dysfunction that, in the investigator's judgment, may interfere with their participation in the study.
• Patients with any other unspecified unstable medical condition.