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.

Mitigating Multi-Sequence 3D Prostate MRI Data Scarcity through Domain Adaptation using Locally-Trained Latent Diffusion Models for Prostate Cancer Detection

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Jul 08, 2025
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Attention-Enhanced Deep Learning Ensemble for Breast Density Classification in Mammography

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Jul 08, 2025
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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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Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation

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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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Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction

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Jun 24, 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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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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