Artificial Intelligence Clinical Trial
Official title:
Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
The aim of this study is to show the physiological changes during manic episode in bipolar mania how much they differentiate from remission and healthy control. Relation of audio-visual features as physiological changes and cognitive functions and clinical variables will be searched. The aim is to find biologic markers for predictors of treatment response via machine learning techniques to be able to reduce treatment resistance and give an idea for personalized treatment of bipolar patients.
The objective of this research protocol is to find audio-visual features which differentiates bipolar mani/ remission/ health/ simulation and predicts treatment response earlier and detect neurocognitive changes during mania/ remission and difference from the healthy control. During hospitalization in every follow up day (0th- 3rd- 7th- 14th- 28th day) and after discharge on the 3rd month, presence of depressive and manic features for patients was evaluated using Young Mania Rating Scale(YMRS) and Montgamery- Asberg Depresyon Scale (MADRS). Audiovisual recording is done by a video camera in every follow up day for patients and for healthy controls which includes also depression and mania simulation. Cambridge Neurophysiological Assessment Battery (CANTAB) were administered to both groups( for patients both in the manic phase and in the remission) to assess neurocognitive functions. ;
| Status | Clinical Trial | Phase | |
|---|---|---|---|
| Completed |
NCT04589078 -
Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
|
||
| 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 |
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 | |
| Recruiting |
NCT06059378 -
Real-life Implementation of an AI-based Optical Diagnosis
|
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
|
||
| Recruiting |
NCT04598997 -
Artificial Intelligence With DEep Learning on COROnary Microvascular Disease
|