Actively Recruiting
A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence
Led by IRCCS Azienda Ospedaliero-Universitaria di Bologna · Updated on 2025-01-09
200
Participants Needed
4
Research Sites
95 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
This is a non-interventional, national, multicenter prospective non-profit observational study aiming at improving the accuracy of risk prediction in multiple myeloma (MM) by applying machine-learning tools for data processing to develop model(s) predicting response to therapy and the probability of early relapse for MM patients.
CONDITIONS
Official Title
A Machine Learning Approach to Connect Multiple Myeloma Complexity to Early Disease Recurrence
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age 63 18 years
- Signed Informed Consent form for study participation and personal data processing
- Diagnosis of active multiple myeloma
You will not qualify if you...
History of severe allergic reactions to study medication Currently pregnant or breastfeeding Recent participation in another clinical trial within the last 30 days Presence of uncontrolled medical conditions that could affect safety
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 4 locations
1
Istituto Romagnolo per lo Studio dei Tumori "Dino Amadori" - IRST IRCCS
Meldola, Forlì-Cesena, Italy, 47014
Not Yet Recruiting
2
IRCCS Azienda Ospedaliero-Universitaria di Bologna
Bologna, Italy, 40138
Actively Recruiting
3
ARNAS "G. Brotzu" di Cagliari
Cagliari, Italy, 09134
Not Yet Recruiting
4
Azienda Ospedaliera Universitaria Federico II
Naples, Italy, 80131
Not Yet Recruiting
Research Team
E
Elena Zamagni, MD, PhD
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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