RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification

RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification

<b>Background:</b> Reinforcement learning (RL) represents a significant advancement in artificial intelligence (AI), particularly for complex sequential decision-making challenges. Its capability to iteratively refine decisions makes it ideal for applications in medicine, such as the det...

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Bibliographic Details
Main Authors: Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Diagnostics
Subjects:
reinforcement learning
cervical cancer
lightweight model
Pap test
classification
diagnosis
Online Access:https://www.mdpi.com/2075-4418/15/3/364
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