Artificial Intelligence Clinical Trial
Official title:
Assessment of Knowledge and Perceptions of Artificial Intelligence in Solid Organ Transplantation
The increasing abundance of clinical, genetic, radiological, and metabolic data in transplantation has led to a growing interest in applying artificial intelligence (AI) tools to optimize immunosuppression and overall patient management. However, the majority of these applications exist only in the preclinical state and the field of artificial intelligence remains unknown to the general public. In view of the potential applications of AI and the growing research interest in this topic, it is essential to assess the knowledge and perceptions of those directly involved in solid organ transplantation. Primary Objective: To assess the knowledge and perceptions of solid organ transplant patients and healthcare professionals working in the field of solid organ transplantation Primary endpoint: - Analysis of verbatim and closed-ended questionnaire data - Comparison of the averages obtained by the subgroups of patients and health professionals and analysis of the verbatim by grouping them by themes
Solid organ transplantation is the treatment of last resort for end-stage organ disease. In France, 51860 patients receive transplants, and the number of candidates awaiting transplantation has doubled in 10 years. At the same time as considerable progress has been made in recent decades, new challenges have emerged. The growing disparity between demand and supply of organs calls for optimal selection and matching of patients and donors. Improving long-term graft and patient survival requires data-driven diagnosis and management of post-transplant complications. The increasing abundance of clinical, genetic, radiological and metabolic data in transplantation has led to growing interest in applying artificial intelligence (AI) tools to optimize immunosuppression and overall patient management. However, the majority of these applications are still in the pre-clinical stage, and the field of artificial intelligence remains largely unknown to the general public. In view of the potential applications of AI and the growing research interest in the subject, it is essential to assess the knowledge and perceptions of those directly involved in solid organ transplantation. This is a prospective, observational, multicenter study. The questionnaire will be submitted face-to-face to healthcare professionals working in solid organ transplantation and solid organ transplant patients at Grenoble Alpes University Hospital. It will be put online on the LimeSurvey platform and offered to healthcare professionals at France's various transplant centers via the federations of each organ specialty, as well as to all organ transplant patients in France via patient associations. The data included will be collected from paper questionnaires and online on the LimeSurvey platform. They will be stored on a secure server at the TIMC research laboratory department. Data will be anonymized for inclusion in the database. An identifier will be assigned to each volunteer at the time of inclusion. Categorical data will be reported as frequency, percentage, and continuous data as mean and standard deviation or median and interquartile range if they do not follow a normal distribution. The normality of quantitative variables will be tested by graphical verification. Continuous variables will be compared using a Student's t test if the conditions of application are valid (or Mann-Whitney if applicable). Categorical variables will be compared using a Chi2 test (or Fisher's test if validity conditions are not met). We consider p values <0.05 to be significant. Statistical analysis will be carried out using RStudio software (version 4.2.1). ;
Status | Clinical Trial | Phase | |
---|---|---|---|
Completed |
NCT04589078 -
Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
|
||
Completed |
NCT03857438 -
Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
|
||
Completed |
NCT04735055 -
Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
|
||
Not yet recruiting |
NCT05452993 -
Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography
|
N/A | |
Not yet recruiting |
NCT04337229 -
Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques
|
N/A | |
Completed |
NCT05687318 -
A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment
|
N/A | |
Recruiting |
NCT06051682 -
Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.
|
N/A | |
Not yet recruiting |
NCT06039917 -
Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions
|
N/A | |
Not yet recruiting |
NCT06362629 -
AI App for Management of Atopic Dermatitis
|
N/A | |
Recruiting |
NCT06059378 -
Real-life Implementation of an AI-based Optical Diagnosis
|
N/A | |
Recruiting |
NCT06164002 -
A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials
|
N/A | |
Completed |
NCT05517889 -
Repeatability and Stability of Healthy Skin Features on OCT
|
||
Completed |
NCT04816981 -
AI-EBUS-Elastography for LN Staging
|
N/A | |
Completed |
NCT05006092 -
Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)
|
N/A | |
Recruiting |
NCT04535466 -
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
|
||
Enrolling by invitation |
NCT04719117 -
Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
|
||
Completed |
NCT04399590 -
Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
|
||
Recruiting |
NCT04126265 -
Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps
|
N/A | |
Recruiting |
NCT06255808 -
Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
|
||
Recruiting |
NCT04131530 -
Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence
|