Application dilemma and solution paths of personalized patient preference predictor
10.12026/j.issn.1001-8565.2025.05.05
- VernacularTitle:个性化患者偏好预测器的应用困境及化解路径
- Author:
Jieran ZHU
1
;
Zhibin LIN
1
Author Information
1. School of Marxism， Guangzhou University of Chinese Medicine， Guangzhou 510006， China
- Publication Type:Journal Article
- Keywords:
artificial intelligence technology;
personalized patient;
preference predictor;
patient autonomy
- From:
Chinese Medical Ethics
2025;38(5):574-581
- CountryChina
- Language:Chinese
-
Abstract:
The personalized patient preference predictor proposed in 2024 has sparked widespread discussion. It mainly integrates machine learning with fine-tuning large language models to extract patients’ medical preferences by training and analyzing patients’ personalized sample data， to achieve better treatment. Combined with the current research situation， this paper pointed out its application dilemma： that is， the risks of inductive and analogical reasoning trigger its technical dilemma in accurate prediction， process explanation， and functional evaluation， ultimately leading to the ethical dilemma of the reduction of subject autonomy. Its solution paths were also clarified， including introducing substantive induction theory and substantive analogy theory to ensure the validity of sample data； implementing technology integration， perspective change， and evaluation system construction to improve the accuracy of prediction； as well as clarifying the priority of human subject status to protect the patient’s subjective autonomy. These showed that the personalized patient preference predictor has important social value and practical significance.
