MedTrace Logo

AI-Predicted Disease Trajectories in Diabetes: A Retrospective Study

NCT06280729 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2024-02-28

No results posted yet for this study

Summary

The study explores the utilization of artificial intelligence (AI) to predict disease progression trajectories in patients with diabetes. By analyzing historical data from a retrospective cohort, we aim to identify patterns and predictors of disease evolution. The approach seeks to enhance personalized treatment strategies and improve outcomes by foreseeing potential complications and disease milestones. The findings could pave the way for more targeted and effective management of diabetes through AI-driven insights.

Conditions

  • Diabetes Mellitus, Type 1
  • Diabetes Mellitus, Type 2

Interventions

OTHER

AI-Analyis

The study will investigate classification (ie logistic regression, decision tree, random forest, support vector machine, K nearest neighbour, naive bayes) ML models and treatment effect estimation ML models (T-learner, X-learner..).

Sponsors & Collaborators

  • IRCCS San Raffaele

    lead OTHER

Principal Investigators

  • Lorenzo Piemonti, MD · IRCCS Ospedale San Raffaele srl

  • Emanuele Bosi, MD · IRCCS Ospedale San Raffaele srl

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-03-01
Primary Completion
2025-03-01
Completion
2026-03-01

Countries

  • Italy

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06280729 on ClinicalTrials.gov