ProtoMAP: prototypical network based few-shot learning for missed abortion prediction.

ABSTRACT: Missed abortion is a prevalent issue in clinical practice, posing both physical risks to the mother and substantial psychological impact. Accurately predicting the risk of missed abortion is essential for guiding timely clinical interventions and safeguarding maternal health. Data on missed abortion are scarce and imbalanced. Given the limited clinical data and the nonlinear interrelationships among multiple features, traditional machine learning methods often fail to capture essential patterns, thereby their prediction performance is suboptimal. This paper proposes a prototype network based on few-shot learning, namely ProtoMAP. The goal is to train a missed abortion prediction model using a limited number of samples, while achieving performance comparable to models trained on large-scale

SUBMITTER: Bo X 

PROVIDER: S-EPMC12465688 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature