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Patients' subjective complaints about pain intensity are difficult to objectively evaluate, and may lead to inadequate pain management, especially in patients with communication difficulties.
Analgesia nociception index (ANI 0-100) and patient-reported numeric rating scale (NRS 0-10) were trained on a convolutional neural network (CNN) model by linking the patients' facial expression with the score. By applying the predicted pain score by the AI model to evaluate pain, it is intended to measure the intensity of pain in an automatic, fast, and objective way for appropriate pain management.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| taking a picture of a painful facial expression | Other | Immediately after surgery, the patient's facial expression and the NRS score and ANI score reported by the patient are checked together. |
| Measure | Description | Time Frame |
|---|---|---|
| Facial expression | Painful facial expression | immediately preoperative, postoperative time |
| analgesia nociception index | ANI score | immediately preoperative, postoperative time |
| numeric rating scale | pain score | immediately preoperative, postoperative time |
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Inclusion Criteria:
Exclusion Criteria:
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Patients who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| InSun Park, MD | Contact | 82317877499 | pis121@hanmail.net |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Seoul National University Bundang Hospital | Recruiting | Seongnam-si | Gyunggi-do | 13620 | South Korea |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38176698 | Derived | Park I, Park JH, Yoon J, Na HS, Oh AY, Ryu J, Koo BW. Machine learning model of facial expression outperforms models using analgesia nociception index and vital signs to predict postoperative pain intensity: a pilot study. Korean J Anesthesiol. 2024 Apr;77(2):195-204. doi: 10.4097/kja.23583. Epub 2024 Jan 5. | |
| 38150126 | Derived |
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| ID | Term |
|---|---|
| D005149 | Facial Expression |
| D000377 | Agnosia |
| D010149 | Pain, Postoperative |
| ID | Term |
|---|---|
| D009633 | Nonverbal Communication |
| D003142 | Communication |
| D001519 | Behavior |
| D010468 | Perceptual Disorders |
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| Park I, Park JH, Yoon J, Song IA, Na HS, Ryu JH, Oh AY. Artificial intelligence model predicting postoperative pain using facial expressions: a pilot study. J Clin Monit Comput. 2024 Apr;38(2):261-270. doi: 10.1007/s10877-023-01100-7. Epub 2023 Dec 27. |
| D019954 |
| Neurobehavioral Manifestations |
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D011183 | Postoperative Complications |
| D010335 | Pathologic Processes |
| D010146 | Pain |