Remisio: Personalized IBD Management Platform

Remisio is a digital platform developed to address the substantial and escalating public health challenge of Inflammatory Bowel Diseases (IBD) in Poland, where the prevalence increased threefold between 2010 and 2020. The platform supports continuous patient monitoring and promotes treatment adherence to facilitate early detection of warning signs and timely interventions to prevent disease exacerbations.
Key Project Components and Functionality:

• Patient's Mobile App: A patient-centered application developed with Dart and the Flutter framework, enabling cross-platform deployment on Android and iOS devices.

  • Features: Weekly surveys, tracking disease history, logging diagnostic tests and meals, planning visits, medication reminders, and symptom reporting.

• Doctor Dashboard: An intuitive, easy-to-navigate interface developed using TypeScript, React, and Tailwind CSS. It provides:

  • An overview of all patients and their therapeutic progress.

  • Access to detailed longitudinal patient data on a plot.

  • Customizable surveys that physicians can adjust to individual treatment needs.

• AI Analytics & Monitoring: The platform integrates machine learning and other methods to enhance clinical decision support.

  • Surveys: Weekly patient surveys generate Crohn's Disease Activity Index (CDAI) scores and Mayo Scores for ulcerative colitis to classify disease activity.

  • Prediction Model: An integrated machine learning model, developed by the poster co-authors, analyzes routine blood, urine, and stool markers to predict disease activity state according to the Mayo scale, achieving 91–97% accuracy.

  • Dietary Analysis: The system identifies a dish from a snapped meal photo, matches it to the Foodon nutritional ontology, and scores its nutrient density and FODMAP load.

  • Future Development: Efforts are underway to integrate continuous wearable devices, including passive sweat-sensing wearables that measure TNF-a, which can distinguish active IBD from healthy controls with high accuracy (AUC approx. 0.96).

Conclusion: Remisio is paving the way for personalized, proactive IBD management by combining patient-reported outcomes, laboratory markers, AI analytics, and future wearable sensing into a single, clinically-oriented workflow. The team plans to begin a pilot study with real patients in collaboration with the SKN Gastroenterologii student research group at Wrocław Medical University to refine usability and validate clinical impact.