Clinical trials: Computer-aided System
Colo-rectal Cancer, Polyp of Colon
Computer Aided Detection of Polyps During Colonoscopy Procedures
The focus of the study is to evaluate impact on Adenomas Per Colonoscopy (APC) with a Computer Aided Detection (CAD) software assisting the gastroenterologist during a colonoscopy procedure.
- Conditions
- Colo-rectal Cancer, Polyp of Colon, Adenomatous Polyps
- Trial name
- NCT04195646
- Testing
- EndoVigilant CAD Software
- Where
- 2 sites in United States
- Volunteers
- 300 people, healthy volunteers welcome
- Sponsor
- EndoVigilant Inc
Prostate Cancer
External Validation of Prostate MRI QCAD/Lyon
Multiparametric magnetic resonance imaging (mpMRI) of the prostate combines T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced imaging.
- Trial name
- DIJON-CAD (NCT03687918)
- Testing
- Assessment of the performances of QCAD/Lyon in characterizing Gleason ≥7 cancers among contoured lesions
- Where
- 7 sites in France
- Volunteers
- 80 people
- Sponsor
- Hospices Civils de Lyon
Cerebrovascular Diseases, Stroke
Computer-Aided Prevention System
Stroke is one of the most frequent and life-threatening diseases in Europe. About four stroke events occur per day in Luxembourg alone, and about 30% of these patients are affected by recurrent stroke within the following five…
- Conditions
- Cerebrovascular Diseases, Stroke, Cardiovascular Diseases, CVD Risk Factors
- Trial name
- CAPSYS (NCT02444715)
- Testing
- Standard care, CAPSYS
- Volunteers
- 94 people
- Sponsor
- Lübomira Spassova
Ovarian Cancer, Ovarian Tumor
AI Analysis of CT Scans to Classify Ovarian Tumours as Benign, Borderline or Malignant Before Surgery
The goal of this observational study is to learn if a computer program can tell what type of ovarian tumour a person has from a CT scan taken before surgery. The program uses artificial intelligence (AI).
- Conditions
- Ovarian Cancer, Ovarian Tumor, Borderline Ovarian Tumor
- Trial name
- OvaClass (NCT07883551)
- Where
- 7 sites in Belgium, Netherlands
- Volunteers
- 1,300 people
- Sponsor
- Catharina Ziekenhuis Eindhoven
Gastric Neoplasm, Artificial Intelligence
Miss Rate of Gastric Neoplasms Under Computer-aided Endoscopy
This prospective randomized trial compares AI-assisted upper gastrointestinal endoscopy with high definition upper gastrointestinal endoscopy in term of missed rate of gastric neoplasm.
- Trial name
- NCT06495645
- Testing
- AI-assisted upper gastrointestinal endoscopy
- Where
- Hong Kong
- Volunteers
- 1,000 people
- Sponsor
- The University of Hong Kong
Dental Caries
Investigation of the Effect of Deep Margin Elevation Technique on the Clinical Performance of Endocrown Restorations Produced by Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) System
The aim of this clinical study is to investigate the impact of the deep margin elevation technique on the clinical performance of CAD/CAM endocrown restorations in deep Class II cavities.
- Trial name
- NCT06222918
- Testing
- Deep Margin Elevation (G-ænial Universal Injectable)
- Where
- Turkey (Türkiye)
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- Hacettepe University
Barrett Esophagus, Barrett Adenocarcinoma
Real-time Computer Aided Detection of Barrett's Neoplasia
In the real-time pilot study, the performance of a recently developed Computer Aided Detection (CADe) system will be investigated in 30 patients during real-time live endoscopic examination.
- Trial name
- NCT05628441
- Testing
- Computer Aided Detection system for Barrett's neoplasia
- Where
- Netherlands
- Volunteers
- 30 people, healthy volunteers welcome
- Sponsor
- Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
Diabetic Retinopathy, Retinal Vein Occlusion
Computer Aided Diagnosis of Multiple Eye Fundus Diseases From Color Fundus Photograph
Blindness can be caused by many ocular diseases, such as diabetic retinopathy, retinal vein occlusion, age-related macular degeneration, pathologic myopia and glaucoma.
- Conditions
- Diabetic Retinopathy, Retinal Vein Occlusion, Retinal Artery Occlusion, Central Serous Chorioretinopathy
- Trial name
- NCT04723160
- Testing
- Software assisted imaging diagnosis
- Where
- 5 sites in China
- Volunteers
- 748 people, healthy volunteers welcome
- Sponsor
- Visionary Intelligence Ltd.
Colorectal Polyp, Colorectal Cancer
Computer-aided Detection During Screening Colonoscopy
Nowadays, colonoscopy is considered the gold standard for the detection of lesions in the colorectal mucosa. However, around 25% of polyps may be missed during the conventional colonoscopy.
- Conditions
- Colorectal Polyp, Colorectal Cancer, Colorectal Adenoma
- Trial name
- NCT05734820
- Testing
- HD- colonoscopy, HD-colonoscopy assisted by AI
- Where
- Ecuador
- Volunteers
- 312 people
- Sponsor
- Instituto Ecuatoriano de Enfermedades Digestivas
Colorectal Cancer, Colorectal Neoplasms
Real-Time CAD for Colonic Neoplasia: A RCT
This study assesses the sensitivity and added benefits of computer-aided detection compared to standard care (white-light) in detecting colon polyps in patients undergoing colonoscopy.
- Trial name
- CAD (NCT05963724)
- Testing
- Real-Time Computer Aided Detection, Stanford Colonoscopy
- Where
- United States
- Volunteers
- 1,100 people
- Sponsor
- Riverside University Health System Medical Center
Maxillofacial Injury
Computer Modeling With Reconstruction of Maxillofacial Skeleton
Investigator initial study to evaluate the use of preoperative computer modeling and the intraoperative navigation to guide reconstruction of the maxillofacial skeleton.
- Trial name
- NCT00583856
- Where
- United States
- Volunteers
- 3 people
- Sponsor
- University of California, Davis
Colorectal Cancer, Colorectal Adenoma
Accuracy of Real Time Characterization in Artificial Intelligence-assisted Colonoscopy
The goal of this substudy is to investigate the accuracy of a computer-aided polyp characterization (CADx) system. The main question[s] it aims to answer are: How high is the specificity of the AI system when characterizing…
- Conditions
- Colorectal Cancer, Colorectal Adenoma, Colorectal Neoplasms
- Trial name
- NCT05754229
- Testing
- AI-assisted colonoscopy
- Where
- 4 sites in Denmark
- Volunteers
- 395 people, healthy volunteers welcome
- Sponsor
- Ismail Gögenur
Gastric Cancer
Evaluation of a Computer-aided Diagnosis System (CADx) in the Early Detection of Gastric Cancer in France. Cancer in France.
Upper gastrointestinal (GI) cancers are one of the most common cancers worldwide. Except for cardia cancers, the incidence of gastric cancer has decreased consistently since 1980, but remains at a high level.
- Trial name
- EGC-France (NCT05928819)
- Testing
- Evaluation of the proportion of gastric neoplastic lesions detected by a computer-aided diagnosis system (CADx) compared with experienced endoscopists.
- Where
- France
- Volunteers
- 120 people
- Sponsor
- Hospices Civils de Lyon
Graves Disease
Methimazole in Graves' Disease - Comparing the Computer-aided Treatment DigiThy Versus Usual Care
The goal of this clinical trial is to compare two methods of guiding methimazole therapy in patients with Graves' disease: methimazole dose adjustments based on a new semi-automated computer-guided treatment (based on a…
- Trial name
- NCT06327828
- Testing
- Semi-automated computer-aided treatment (Digital Thyroid, DigiThy), Usual care
- Where
- Austria
- Volunteers
- 52 people
- Sponsor
- Medical University of Graz
Carotid Atherosclerosis, Peripheral Arterial Disease
Non-invasive Computer-Aided Phenotyping of Vasculopathy
The investigators use MRI and/or CT to evaluate the extent, as well as, the structure, composition, and functional aspects of atherosclerotic plaques in human carotid and femoral arteries in patients scheduled to undergo an…
- Trial name
- Q-CAMP (NCT02143102)
- Where
- 2 sites in United States
- Volunteers
- 125 people
- Sponsor
- Elucid Bioimaging Inc.
Esophagogastroduodenoscopy
AQCS for Detection of Early Cancer and Precancerous Lesions on Upper Gastrointestinal Tract
The purpose of our study was to assess the performance of esophagogastroduodenoscopy automatic quality-control system in real-time quality control of EGD.
- Trial name
- NCT04720924
- Testing
- Computer-aided Real-time Automatic Quality-control System
- Where
- 6 sites in China
- Volunteers
- 1,840 people
- Sponsor
- Shandong University
Colonoscopy, Colorectal Neoplasms
Interest of Artificial Intelligence in Cancer Screening Colonoscopy
Artificial Intelligence (AI) to predict the histology of polyps per colonoscopy, offers a promising solution to reduce variation in colonoscopy performance.
- Conditions
- Colonoscopy, Colorectal Neoplasms, Intestinal Polyps, Deep Learning
- Trial name
- IA COLO (NCT04921488)
- Testing
- screening colonoscopy
- Where
- 5 sites in France
- Volunteers
- 194 people
- Sponsor
- University Hospital, Bordeaux
Endotracheal Tube, Nasogastric Tube
AI-Assisted Chest X-Ray for Misplaced Endotracheal and Nasogastric Tubes and Pneumothorax in Emergency and Critical Care Settings
Background Advancements in artificial intelligence (AI) have driven significant breakthroughs in computer-aided detection (CAD) for chest X-ray imaging.
- Conditions
- Endotracheal Tube, Nasogastric Tube, Pneumothorax
- Trial name
- NCT06842043
- Testing
- AI-assisted model
- Where
- Taiwan
- Volunteers
- 10,900 people
- Sponsor
- National Taiwan University Hospital
Colorectal Cancer
Clinical Validation of PolyDeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System. Polydeep Advance 3
This study is a clinical validation of PolyDeep, a computer-aided polyp detection (CADe) and characterization (CADx) system. PolyDeep Advance 3 is a multicentric randomized clinical trial comparing high definition colonoscopy…
- Trial name
- NCT05513261
- Testing
- High definition colonoscopy (standard colonoscopy) in Adenoma Detection Rate, PolyDeep assisted high definition colonoscopy (CAD system) in Adenoma Detection Rate
- Where
- 3 sites in Spain
- Volunteers
- 857 people
- Sponsor
- Fundacin Biomedica Galicia Sur
Colonic Polyp
Computer Aided Polyp Detection (C3PO) Trial
Computer aided detection (CADe) algorithms have been developed to overcome human errors and assist endoscopists in detecting more polyps during colonoscopy.
- Trial name
- NCT04777019
- Testing
- Not applicable as standard of care Colonoscopy
- Sponsor
- The University of Texas Health Science Center, Houston