PSOA-LSTM: a hybrid attention-based LSTM model optimized by particle swarm optimization for accurate lung cancer incidence forecasting in China (1990–2021)

PSOA-LSTM: a hybrid attention-based LSTM model optimized by particle swarm optimization for accurate lung cancer incidence forecasting in China (1990–2021)

BackgroundAccurate forecasting of lung cancer incidence is crucial for early prevention, effective medical resource allocation, and evidence-based policymaking.ObjectiveThis study proposes a novel deep learning framework—PSOA-LSTM—that integrates Particle Swarm Optimization (PSO) with an attention-b...

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Bibliographic Details
Main Authors: Nannan Xu, Guang Yang, Linlin Ming, Jiefei Dai, Kun Zhu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Medicine
Subjects:
lung cancer
healthcare forecasting
LSTM
attention mechanism
particle swarm optimization
time-series prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1620257/full
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https://www.frontiersin.org/articles/10.3389/fmed.2025.1620257/full

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