Clinical trials: CADe
Colonic Polyp, Colonic Adenoma
Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy
The goal of this trial is to determine whether use of a Computer Assisted Detection (CADe) programme leads to an increase in ADR for either units or individual colonoscopists, independent of setting or expertise
- Conditions
- Colonic Polyp, Colonic Adenoma, Colo-rectal Cancer
- Trial name
- NAIAD (NCT05870332)
- Testing
- GI Genius (GIG)
- Where
- United Kingdom
- Volunteers
- 4,000 people, healthy volunteers welcome
- Sponsor
- King's College Hospital NHS Trust
Colorectal Cancer (CRC) Screening
A Novel Multi-functional Artificial Intelligence System on Treatment Efficacy and Implementation in Colonoscopy
To overcome non-neoplastic polyp (NNP) resections, computer-aided diagnosis (CADx) systems have been developed. In a meta-analysis, the performance of CADx systems was superior to endoscopists.
- Trial name
- mAInstream (NCT07844252)
- Testing
- CADe/CADx
- Volunteers
- 2,818 people, healthy volunteers welcome
- Sponsor
- Chinese University of Hong Kong
Gastric Neoplasia
Efficacy of CADe System in Detecting Gastric Neoplasia
Gastric cancer remains the 5th most common cancers worldwide. It also ranked 5th in the cancer related mortality, causing more than 650'000 deaths per year.
- Trial name
- NCT07395570
- Testing
- CADe System
- Where
- Hong Kong
- Volunteers
- 260 people
- Sponsor
- Chinese University of Hong Kong
Artificial Intelligence
Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
One fourth of colorectal neoplasias are missed during screening colonoscopies-these can develop into colorectal cancer (CRC). In the last couple of years, Artificial Intelligence Deep learning systems were introduced in the…
- Trial name
- NOISE (NCT04399590)
- Testing
- Interficial Intelligence
- Where
- Italy
- Volunteers
- 40 people
- Sponsor
- Istituto Clinico Humanitas
Covid19
Cardiac Assessment After Covid-19 Disease in Elite Altheltic Population
COVID-19 infection coud induce cardiac injuries. Before returning to sport, cardiac evaluation is recommended by sports federations, based on the precautionary principle and the opinion of expert consensus.
- Trial name
- CADE (NCT04653857)
- Where
- France
- Volunteers
- 250 people
- Sponsor
- University Hospital, Montpellier
Amputation Wound, Peripheral Arterial Disease
Wound Imaging Study to Gather Clinical References for a Device to Assist Selecting Level-of-amputation in PAD Patients
This is a proof-of-concept study to collect images to train a CADe algorithm to predict the correct level of amputation in individuals scheduled for amputation secondary to PAD.
- Trial name
- WISCR (NCT03611361)
- Testing
- SpectralMD DeepView Wound Imaging System 2.0
- Where
- United States
- Volunteers
- 55 people
- Sponsor
- SpectralMD
Colon Polyp, Colon Neoplasm
A Clinical Study To Measure The Effect Of Use Of Artificial Intelligence (AI) Enabled Computer Aided Detection (CADe) Assistance Software In Detecting Colon Polyps During Standard Colonoscopy Procedures
EndoVigilant software device augments existing colonoscopy procedure video in real-time by highlighting colon polyps and mucosal abnormalities.
- Conditions
- Colon Polyp, Colon Neoplasm, Colon Adenoma
- Trial name
- ColonCADe (NCT04555135)
- Testing
- EndoVigilant Software
- Where
- 4 sites in United States
- Volunteers
- 769 people
- Sponsor
- EndoVigilant Inc
Colorectal Cancer
Clinical Validation of Polydeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System
This study is a clinical validation of Polydeep, a computer-aided polyp detection (CADe) and characterization (CADx) system. Polydeep Advance 1 is an unicentric prospective diagnostic tests trial with a paired study design.
- Trial name
- NCT05514301
- Testing
- Sensitivity of Polydeep vs high experienced endoscopists for colorectal polyp detection
- Where
- Spain
- Volunteers
- 205 people
- Sponsor
- Fundacin Biomedica Galicia Sur
Colorectal Cancer
Clinical Validation of PolyDeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System. Polydeep Advance 2.
This study is a clinical validation of PolyDeep, a computer-aided polyp detection (CADe) and characterization (CADx) system. PolyDeep Advance 2 is a multicentric randomized clinical trial with a tandem colonoscopy design.
- Trial name
- NCT05512793
- Testing
- Standard technique First colonoscopy without PolyDeep, Combination technique First colonoscopy with PolyDeep
- Where
- 3 sites in Spain
- Volunteers
- 260 people
- Sponsor
- Fundacin Biomedica Galicia Sur
Adenoma Colon, Colonic Adenoma
Accuracy of Endo-aid in Consecutive Patients Referred for Colonoscopy
The goal of this clinical trial is to evaluate the diagnostic yield of CADe in a consecutive population undergoing colonoscopy. The main question it aims to answer is the Adenoma Detection Rate (ADR).
- Trial name
- ACCENDO-Colo (NCT05862948)
- Testing
- ENDO-Aid by Olympus
- Where
- 2 sites in Italy
- Volunteers
- 1,160 people
- Sponsor
- Fondazione Poliambulanza Istituto Ospedaliero
Sessile Serrated Lesion, CADe
USAGE OF ARITIFICIAL INTELLIGENCE IN AIDING WITH COLONIC SESSILE SERRATED LESIONS DETECTION AND DIAGNOSIS (AI-SSL)
The aim of this study is to is to evaluate if a real-time Computer Aided Detection (CADe) system can help improve the detection of SSL(sessile serrated lesions) versus a conventional colonoscopy (CC) using white light…
- Trial name
- AI-SSLD (NCT07650344)
- Testing
- usage of CADe system
- Where
- 3 sites in Singapore
- Volunteers
- 628 people, healthy volunteers welcome
- Sponsor
- National Healthcare Group, Singapore
Quality Indicators, Health Care, Artificial Intelligence (AI)
Artificial Intelligence in Colonoscopy
Colorectal cancer is the second most common malignancy in the countries of the European Union. Colonoscopy is the primary method for detecting and preventing the development of colorectal cancer is endoscopic examination.
- Conditions
- Quality Indicators, Health Care, Artificial Intelligence (AI), Colonoscopy Diagnostic Techniques and Procedures
- Trial name
- NCT06786793
- Testing
- Computer-aided detection (CADe)
- Where
- 2 sites in Poland
- Volunteers
- 630 people
- Sponsor
- Jagiellonian University
Quality Indicators, Health Care, Colonoscopy Diagnostic Techniques and Procedures
The Implementation of Computer-aided Detection in Training Improves the Quality of Future Colonoscopies
Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment.
- Conditions
- Quality Indicators, Health Care, Colonoscopy Diagnostic Techniques and Procedures, Artificial Intelligence (AI)
- Trial name
- NCT06623331
- Testing
- AI-enhanced endoscopy training, Conventional endoscopy training
- Where
- Poland
- Volunteers
- 6,000 people
- Sponsor
- Jagiellonian University
Surveillance Endoscopy for Colorectal Cancer, Artificial Intelligence
Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)
Evaluation of an artificial intelligence system for polyp detection (CADe)
- Conditions
- Surveillance Endoscopy for Colorectal Cancer, Artificial Intelligence, Polyps of Colon, CADe
- Trial name
- SMARTIE (NCT05006092)
- Testing
- ENDOMIND
- Where
- Germany
- Volunteers
- 1,149 people, healthy volunteers welcome
- Sponsor
- Wuerzburg University Hospital
Breast Cancer
Artificial Intelligence for breaST canceR scrEening in mAMmography (AI-STREAM)
This prospective study aims to generate real-world evidence on the overall benefits and disadvantages of using Lunit INSIGHT MMG AI based CADe/x for breast cancer detection in a population-based breast cancer screening program in…
- Trial name
- NCT05024591
- Testing
- Lunit INSIGHT MMG CADe/x for medical imaging
- Where
- 5 sites in South Korea
- Volunteers
- 25,008 people
- Sponsor
- Kyung Hee University Hospital at Gangdong
High Risk Cancer, Lung Cancer
Retrospective Clinical Trial Comparing Radiologists' Diagnosis Accuracy in Lung Cancer Screening Population With and Without the Help of an AI/ML Tech-based SaMD
This is a two arm, randomized, controlled, blinded, multi-case multi reader (MRMC), retrospective study for the evaluation of the efficacy and safety of an AI/ML technology-based CADe/x developed to detect, localize and…
- Trial name
- RELIVE (NCT06751576)
- Testing
- Median LCS
- Where
- 5 sites in United States, Spain
- Volunteers
- 480 people, healthy volunteers welcome
- Sponsor
- Median Technologies
Colorectal Cancer
Safety and Efficacy of the Olympus CADe System in Real-time Colonoscopy
This is a prospective, multicenter, randomized Trial to assess the safety and efficacy of the Olympus Endoscopy Computer-Aided Detection (CADe) system, OIP-1, in the detection of colorectal neoplasia's during real-time…
- Trial name
- EuroCADe (NCT05943288)
- Testing
- OIP-1
- Where
- 6 sites in Belgium, Germany and 2 more
- Volunteers
- 850 people
- Sponsor
- Olympus Europe SE & Co. KG
Colorectal Neoplasms, Colorectal Cancer
A Study Comparing Standard and AI-Assisted Colonoscopies for Detecting and Characterizing Colorectal Lesions in Adults Aged 50-74 Undergoing Cancer Screening
The goal of this clinical trial is to determine whether using artificial intelligence (AI) can improve the detection and characterization of abnormal growths (polyps) during colonoscopy in adults aged 50 to 74 years who are…
- Conditions
- Colorectal Neoplasms, Colorectal Cancer, Adenoma Colon Polyp
- Trial name
- NCT07125300
- Testing
- Artificial Intelligence-Assisted Colonoscopy
- Where
- Spain
- Volunteers
- 368 people, healthy volunteers welcome
- Sponsor
- Javier Santos Fernández
High Risk Cancer
Standalone Observational Study Assessing the Performance of an AI/ML Tech-based SaMD on Chest LDCT Images (REALITY)
This is a Multinational, Multicenter, retrospective study for the evaluation of the standalone efficacy and safety of an Artificial Intelligence/Machine Learning (AI/ML) technology-based end-to-end Computer assisted…
- Trial name
- REALITY (NCT06576232)
- Testing
- Median LCS
- Where
- 5 sites in United States, Spain
- Volunteers
- 1,147 people, healthy volunteers welcome
- Sponsor
- Median Technologies
Colonic Adenoma, Adenoma
Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in Follow-up Patients in a Screening Setting
The goal of this clinical trial is to evaluate the diagnostic yield of CADe in a consecutive population undergoing colonoscopy. The main question it aims to answer is the Adenoma Detection Rate (ADR).
- Conditions
- Colonic Adenoma, Adenoma, Polyp of Colon
- Trial name
- GENIAL-CO FU (NCT06160466)
- Testing
- CADe colonoscopy using GI Genius device, White light
- Where
- Italy
- Volunteers
- 1,156 people
- Sponsor
- Fondazione Poliambulanza Istituto Ospedaliero