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Found 7 papers, 1 papers with code
MedMamba: Vision Mamba for Medical Image Classification
To demonstrate the potential of MedMamba, we conducted extensive experiments using 14 publicly available medical datasets with different imaging techniques and two private datasets built by ourselves.
Adversarial Masked Image Inpainting for Robust Detection of Mpox and Non-Mpox
In addition, we demonstrated the drawbacks of classification models and buttressed the potential of MIM through clinical validation.
SFUSNet: A Spatial-Frequency domain-based Multi-branch Network for diagnosis of Cervical Lymph Node Lesions in Ultrasound Images
The objective of this work is to diagnose cervical lymph node lesions in ultrasound images by leveraging a deep learning model.
U-SEANNet: A Simple, Efficient and Applied U-Shaped Network for Diagnosis of Nasal Diseases on Nasal Endoscopic Images
Our findings suggest U-SEANNet is the state-of-the-art model for nasal diseases diagnosis in endoscopic images.
Ultrafast-and-Ultralight ConvNet-Based Intelligent Monitoring System for Diagnosing Early-Stage Mpox Anytime and Anywhere
Due to the lack of more efficient diagnostic tools for monkeypox, its spread remains unchecked, presenting a formidable challenge to global health.
Ear-Keeper: Real-time Diagnosis of Ear Lesions Utilizing Ultralight-Ultrafast ConvNet and Large-scale Ear Endoscopic Dataset
Deep learning-based ear disease diagnosis technology has proven effective and affordable.
Mpox-AISM: AI-Mediated Super Monitoring for Mpox and Like-Mpox
With the help of the Internet and communication terminal, Mpox-AISM can perform a real-time, low-cost, and convenient diagnosis for earlier-stage mpox in various real-world settings, thereby effectively curbing the spread of mpox virus.
