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.

T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR Imaging

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Nov 11, 2024
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MPBD-LSTM: A Predictive Model for Colorectal Liver Metastases Using Time Series Multi-phase Contrast-Enhanced CT Scans

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Dec 02, 2024
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Advanced Hybrid Deep Learning Model for Enhanced Classification of Osteosarcoma Histopathology Images

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Oct 29, 2024
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MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel-Spatial Attention for Skin Lesion Segmentation

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Dec 02, 2024
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Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy

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Nov 25, 2024
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Cancer-Net SCa-Synth: An Open Access Synthetically Generated 2D Skin Lesion Dataset for Skin Cancer Classification

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Nov 08, 2024
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Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2

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Nov 24, 2024
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CCIS-Diff: A Generative Model with Stable Diffusion Prior for Controlled Colonoscopy Image Synthesis

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Nov 19, 2024
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An Explainable Attention Model for Cervical Precancer Risk Classification using Colposcopic Images

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Nov 14, 2024
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Performance of a large language model-Artificial Intelligence based chatbot for counseling patients with sexually transmitted infections and genital diseases

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Dec 11, 2024
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