cancer detection


Cancer detection using Artificial Intelligence (AI) involves leveraging advanced machine learning algorithms and techniques to identify and diagnose cancer from various medical data sources. The goal is to enhance early detection, improve diagnostic accuracy, and potentially reduce the need for invasive procedures.

Style transfer as data augmentation: evaluating unpaired image-to-image translation models in mammography

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Feb 04, 2025
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Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge

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Jan 26, 2025
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Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation Embeddings

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Feb 05, 2025
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Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios

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Jan 29, 2025
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The Potential of Convolutional Neural Networks for Cancer Detection

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Dec 24, 2024
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A Retrospective Systematic Study on Hierarchical Sparse Query Transformer-assisted Ultrasound Screening for Early Hepatocellular Carcinoma

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Feb 06, 2025
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RadHop-Net: A Lightweight Radiomics-to-Error Regression for False Positive Reduction In MRI Prostate Cancer Detection

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Jan 03, 2025
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Statistical Verification of Linear Classifiers

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Jan 24, 2025
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SYN-LUNGS: Towards Simulating Lung Nodules with Anatomy-Informed Digital Twins for AI Training

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Feb 28, 2025
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Registration-Enhanced Segmentation Method for Prostate Cancer in Ultrasound Images

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Feb 02, 2025
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