Clinical trials: Diagnostic Screening Programs
Pancreatic Ductal Adenocarcinoma, Familial Pancreatic Cancer
A Study of IMMray™ PanCan-d Test for Early Detection of Pancreatic Cancer in High-risk Groups
PanFAM-1 is a clinical study for early detection of pancreatic cancer in high-risk groups. The goals of the study are to assess the performance and diagnostic accuracy of the IMMray™ PanCan-d test compared to standard-of-care…
- Conditions
- Pancreatic Ductal Adenocarcinoma, Familial Pancreatic Cancer, FAMMM - Familial Atypical Mole Malignant Melanoma Syndrome
- Trial name
- NCT03693378
- Where
- 21 sites in United States, Canada and 3 more
- Volunteers
- 1,349 people, healthy volunteers welcome
- Sponsor
- Immunovia, Inc.
Plasmodium Falciparum Malaria
Mass Screening and Treatment for Reduction of Falciparum Malaria
In this project, the investigators aim at an operational research deployment of Ultrasensitive Rapid Diagnostic Test (URDT) -based Mass Screening and Treatment (MSAT) in the Malaria Elimination Task Force (METF) elimination…
- Trial name
- MSAT (NCT04093765)
- Testing
- Ultrasensitive Rapid Diagnostic Test (URDT), Antimalarials
- Where
- Thailand
- Volunteers
- 5,542 people, healthy volunteers welcome
- Sponsor
- University of Oxford
Breast Cancer, Benign Breast Disease
Evaluating Scaleup of an Adapted Breast Cancer Early Diagnosis Program in Rwanda
Breast cancer incidence is increasing in low- and middle-income countries (LMICs) and breast cancer mortality is high in these regions largely due to late stage diagnoses.
- Conditions
- Breast Cancer, Benign Breast Disease, Cervix Cancer
- Trial name
- NCT05364138
- Where
- Rwanda
- Volunteers
- 2,357 people, healthy volunteers welcome
- Sponsor
- Brigham and Women's Hospital
Artificial Intelligence, Diagnostic Imaging
Real-time Artificial Intelligence System for Detecting Multiple Ocular Fundus Lesions by Ultra-widefield Fundus Imaging
This prospective multicenter study will evaluate the efficacy of a real-time artificial intelligence system for detecting multiple ocular fundus lesions by ultra-widefield fundus imaging in real-world settings.
- Conditions
- Artificial Intelligence, Diagnostic Imaging, Abnormality of the Fundus, Diagnostic Screening Programs
- Trial name
- NCT04859634
- Testing
- Taking an ultra-widefield fundus image
- Where
- China
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University