# Recent Advances in Medical Image Classification

Source: [Recent Advances in Medical Image Classification](<https://www.sota2.com/research/paper/68fa79331e209131cea7c975>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:54:52.275Z

Authors: Loan Dao, Ngoc Quoc Ly

Published: 2025-06-04T16:20:26.000Z

## Abstract

Medical image classification is crucial for diagnosis and treatment, benefiting significantly from advancements in artificial intelligence. The paper reviews recent progress in the field, focusing on three levels of solutions: basic, specific, and applied. It highlights advances in traditional methods using deep learning models like Convolutional Neural Networks and Vision Transformers, as well as state-of-the-art approaches with Vision Language Models. These models tackle the issue of limited labeled data, and enhance and explain predictive results through Explainable Artificial Intelligence.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2506.04129>)

[PDF](<https://arxiv.org/pdf/2506.04129.pdf>)