A Study on the Quantification and Management System of Pain Using Various Recognition Technologies Based on Artificial Intelligence
Not Applicable
Recruiting
- Conditions
- Symptoms, signs and abnormal clinical and laboratory findings, NEC
- Registration Number
- KCT0008684
- Lead Sponsor
- Hallym University Medical Center- Chuncheon
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 2000
Inclusion Criteria
Headache patients who visited Chuncheon Sacred Heart Hospital (outpatient, hospitalized, emergency room patients)
- For adult men and women aged 19 to 80
Exclusion Criteria
1. Patients who refuse to participate in the study
2. Patients who are unable to express their intention due to weakening of their mind and body, or who are unable to conduct surveys or questions and answers
3. Patients under the age of 19 or over 80
Study & Design
- Study Type
- Interventional Study
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method PAIN SCALE;Patient video;Patient voice
- Secondary Outcome Measures
Name Time Method Electrocardiography
Related Research Topics
Explore scientific publications, clinical data analysis, treatment approaches, and expert-compiled information related to the mechanisms and outcomes of this trial. Click any topic for comprehensive research insights.
What molecular mechanisms underlie AI-based pain quantification in clinical settings?
How does AI-driven multi-modal pain recognition compare to traditional assessment tools in efficacy and accuracy?
Are there specific biomarkers that enhance AI model performance for pain management in NEC patients?
What adverse events are associated with AI-integrated pain management systems and how are they mitigated?
What combination therapies show promise with AI-based pain quantification for improved patient outcomes?