BRIDGING THE GAP: EXPLORING THE ACCEPTANCE OF ARTIFICIAL INTELLIGENCE PREDICTIONS IN FERTILITY TREATMENT BY PATIENTS

Abstract

Background: As Artificial Intelligence (AI) becomes increasingly integrated into healthcare, it becomes important to understand the viewpoint of the patients, as they are the main stakeholders in healthcare management. In reproductive medicine, predictive AI is demonstrating its role in the management of subfertility treatment. However, the viewpoint of the patients remains unexplored.

The Objective of this study was to explore the acceptance of using AI predictions in the treatment of subfertility among female patients seeking consultations.

Material and methods: An exploratory qualitative study was conducted with individual semistructured interviews of sixteen female patients undergoing subfertility treatment at Dr. Rehmatullah's Hospital, Gojra. After taking informed consent, data were collected upon data saturation from June 2024 to August 2024. Interview transcripts were transcribed, translated with validation, and analysed for emerging themes using Braun and Clarke’s steps of thematic analysis. 

Results: Data analysis revealed 6 themes and 15 codes, including AI accuracy, need for clinician presence, transparency and clarity of process, data privacy concerns, and patient education. The study participants highlighted both hope as well as concerns for using AI for predictive analysis in subfertility treatment.

Conclusion: This study highlights that patient acceptance of Artificial Intelligence in fertility care is deeply linked to trust, transparency, clinician involvement, and ethical reassurance.