The study aimed to evaluate the effectiveness of an artificial intelligence-based educational guide to prevent surgical site infection among women delivering via cesarean section.

Research hypotheses:

H0: An artificial intelligence-based educational guide will not have any effect on reducing the rate of surgical site infection among women delivering via caesarean section.

H1: An artificial intelligence-based educational guide will have a significant positive effect on reducing the rate of surgical site infection among women delivering via cesarean section.

A purposive sample of 300 CS delivered women was divided randomly by using computer-generated randomization. into a control and intervention group, 150 women each. The control group received standard care. The intervention group received standard care plus the Artificial Intelligence guide

• After discharge, the researcher contacts study subjects every day by WhatsApp and phone call for any questions and to remind them of the upcoming follow-up visit.
• Women were asked to photograph the incision site and send it via WhatsApp using an end-to-end encrypted messaging platform to evaluate the wound condition. All photos were deleted immediately after completing the study for women's privacy.
• At the 10th postoperative day (±3 days), a follow-up was performed in the Outpatient Clinic because the majority of SSIs developed between POD5 and POD10, and due to the importance of timely identification and referral of SSIs.
• According to the study protocol, all women were followed until 30 days after CS. Follow-up was performed in the outpatient clinic, and post-CS SSI screening questions were asked, a physical examination of the patient and determined whether the patient had an SSI as per the Centers for Disease Control and Prevention definition.

Surgical site infections (SSIs) remain a significant concern in obstetric care, particularly following cesarean sections (CS), which are among the most frequently performed surgical procedures worldwide. SSIs not only prolong hospital stays but also increase healthcare costs and contribute to maternal morbidity. Emerging technologies, particularly artificial intelligence (AI), offer promising avenues for enhancing patient education and infection prevention strategies. Recent research demonstrated the potential of AI in healthcare education and infection control. A recent study found that AI-based educational programs significantly improved patients' knowledge and adherence to infection prevention protocols, leading to a 50% reduction in SSI rates post-cesarean section.

Many women, particularly those in rural or underserved communities, have limited access to healthcare professionals and postoperative follow-up care. AI-based educational tools, which can be delivered via mobile applications, SMS alerts, or digital platforms, have the potential to overcome geographical and economic barriers. This study supports the scalability and accessibility of AI-driven health education, particularly for vulnerable populations who may otherwise lack essential postoperative guidance

Inclusion Criteria:

• Women aged 20-60 years who delivered via cesarean section (CS).
• Own a smartphone with internet access.
• Have basic digital literacy, defined as the ability to use mobile applications, read text messages, and communicate via WhatsApp or similar platforms.
• Agree to participate voluntarily and provide informed consent.

Exclusion Criteria:

• Women with severe comorbid medical or psychiatric conditions that may affect their participation or comprehension.

  • Women without smartphone access or with limited digital skills that prevent them from interacting with the AI-based educational guide.
  • Women with communication difficulties (e.g., hearing or speech impairment) that hinder engagement with the intervention.

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