# The acceptability to patients with macular disease to have retreatment decisions being made by artificial intelligence

## TL;DR

This study explores whether patients with macular disease accept artificial intelligence (AI) in making treatment decisions based on retinal images.

## Contribution

The study provides novel insights into patient acceptance of AI in clinical decision-making for macular disease.

## Key findings

- Patients with macular disease find AI acceptable for assessing retinal images.
- Error rate and result verification were the most important factors for patient acceptance.
- Patients did not prefer human or AI for the first or second reader.

## Abstract

Artificial Intelligence (AI) refers to a system that can take input data and subsequently provide a prediction-based output. In some instances, these systems can provide a recommendation for a clinical decision. Such systems are being developed to analyse retinal images and to determine if there is active retinal disease with a view to directly influencing treatment decisions. This study looks at whether AI-based decision making is acceptable to patients with macular disease.

The Macular Society has a monthly newsletter which it sends out to its members and subscribers in which views were canvassed. They were offered participation in a conjoint analysis exploring human or AI decision making, the error rate, the time to follow up and whether the scans were double read by a human or AI tool. Options were presented in a random order and participants were asked to rank the suitability of different scenarios in order of preference.

The task was completed by 181 participants. The two most important factors were the error rate (p < 0.0001) and whether the results were being checked (p < 0.0001). Participants did not state a preference for the first and/or second reader being either human or AI and there was a non-significant trend for rapid turnaround.

Patients with macular disease find AI to be acceptable in the assessment of retinal images. The most important factors to patients relate to the accuracy of the decision making.