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.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Clinical Pathology Analysis

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Dec 12, 2024
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LQ-Adapter: ViT-Adapter with Learnable Queries for Gallbladder Cancer Detection from Ultrasound Image

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Nov 30, 2024
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Deep BI-RADS Network for Improved Cancer Detection from Mammograms

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Nov 16, 2024
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Improved joint modelling of breast cancer radiomics features and hazard by image registration aided longitudinal CT data

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Jan 12, 2025
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Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology

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Nov 14, 2024
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MRANet: A Modified Residual Attention Networks for Lung and Colon Cancer Classification

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Dec 23, 2024
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SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation

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Dec 11, 2024
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Effect sizes as a statistical feature-selector-based learning to detect breast cancer

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Nov 11, 2024
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Enhancing Skin Cancer Diagnosis (SCD) Using Late Discrete Wavelet Transform (DWT) and New Swarm-Based Optimizers

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Nov 30, 2024
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An Attention-Guided Deep Learning Approach for Classifying 39 Skin Lesion Types

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Jan 10, 2025
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