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.

MEGANet-W: A Wavelet-Driven Edge-Guided Attention Framework for Weak Boundary Polyp Detection

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Jul 03, 2025
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A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs

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Jul 02, 2025
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Detection of Breast Cancer Lumpectomy Margin with SAM-incorporated Forward-Forward Contrastive Learning

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Jun 26, 2025
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Devising a solution to the problems of Cancer awareness in Telangana

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Jun 26, 2025
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Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction

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Jun 24, 2025
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Learning from Anatomy: Supervised Anatomical Pretraining (SAP) for Improved Metastatic Bone Disease Segmentation in Whole-Body MRI

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Jun 24, 2025
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Advanced cervical cancer classification: enhancing pap smear images with hybrid PMD Filter-CLAHE

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Jun 18, 2025
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Detecting malignant dynamics on very few blood sample using signature coefficients

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Jun 10, 2025
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A Cytology Dataset for Early Detection of Oral Squamous Cell Carcinoma

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Jun 11, 2025
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BreastDCEDL: Curating a Comprehensive DCE-MRI Dataset and developing a Transformer Implementation for Breast Cancer Treatment Response Prediction

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Jun 13, 2025
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