Construction and Implementation of Procedural Nursing System for General Surgery Laparoscopic Surgery Based on Deep...

Area of Science:

• Medical Informatics
• Surgical Nursing
• Artificial Intelligence in Healthcare

Background:

• Laparoscopic surgery in general surgery requires effective nursing management.
• Traditional nursing methods may not fully optimize patient outcomes.
• Deep learning offers potential for advanced procedural nursing systems.

Purpose of the Study:

• To construct and evaluate a deep learning-based procedural nursing system for general surgery laparoscopic procedures.
• To compare the effectiveness of this system against routine nursing.

Main Methods:

• 150 general surgery laparoscopic patients were divided into a control group (routine nursing) and a study group (deep learning system).
• Nursing quality, pain scores (VAS), postoperative recovery, and complication incidence were assessed.
• Logistic regression was used for multivariate analysis of risk factors for complications.

Main Results:

• The deep learning-based system significantly improved nursing quality and reduced patient pain (VAS scores).
• The incidence of postoperative complications was lower in the study group compared to the control group.
• Underlying diseases and routine nursing were identified as risk factors for complications.

Conclusions:

• The deep learning-based procedural nursing system enhances care quality and patient recovery in general surgery laparoscopic procedures.
• The system effectively reduces pain and complication rates.
• Targeted interventions for underlying diseases and routine nursing are crucial for preventing complications.