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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: May 02, 2024
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Machine learning and new insights for breast cancer diagnosis.
Ya Guo et al. J Int Med Res 2024 52(4) 3000605241237867
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Artificial Intelligence-Powered Mammography: Navigating the Landscape of Deep Learning for Breast Cancer Detection.
Sahem Al Muhaisen et al. Cureus 2024 16(3) e56945
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Deep Learning in Breast Cancer Imaging: State of the Art and Recent Advancements in Early 2024.
Alessandro Carriero et al. Diagnostics (Basel) 2024 14(8)
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Artificial Intelligence for breast cancer detection: Technology, challenges, and prospects.
Oliver Díaz et al. Eur J Radiol 2024 175111457
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A Semiautonomous Deep Learning System to Reduce False-Positive Findings in Screening Mammography.
Stefano Pedemonte et al. Radiol Artif Intell 2024 e230033
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Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.
Sena Alaeikhanehshir et al. Cancer Imaging 2024 24(1) 48
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Prediction and Diagnosis of Breast Cancer Using Machine and Modern Deep Learning Models.
Seeta Devi et al. Asian Pac J Cancer Prev 2024 25(3) 1077-1085
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The promise of AI in personalized breast cancer screening: are we there yet?
Despina Kontos et al. Nat Rev Clin Oncol 2024
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Adaptive Machine Learning Approach for Importance Evaluation of Multimodal Breast Cancer Radiomic Features.
Giulio Del Corso et al. J Imaging Inform Med 2024
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A novel machine learning prediction model for metastasis in breast cancer.
Huan Li et al. Cancer Rep (Hoboken) 2024 7(3) e2006
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Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race.
Galvin Khara et al. Commun Med (Lond) 2024 4(1) 21
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Are better AI algorithms for breast cancer detection also better at predicting risk? A paired case-control study.
Ruggiero Santeramo et al. Breast Cancer Res 2024 26(1) 25
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Deep-learning model to improve histological grading and predict upstaging of atypical ductal hyperplasia / ductal carcinoma in situ on breast biopsy.
Chung-Yen Huang et al. Histopathology 2024
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Explainable machine learning for breast cancer diagnosis from mammography and ultrasound images: a systematic review.
Daraje Kaba Gurmessa et al. BMJ Health Care Inform 2024 31(1)
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Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy.
Omar Falou et al. Sci Rep 2024 14(1) 2340
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Artificial intelligence for triaging of breast cancer screening mammograms and workload reduction: A meta-analysis of a deep learning software.
Debora Xavier et al. J Med Screen 2023 9691413231219952
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Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.
Jinyu Shi et al. BMC Med 2023 21(1) 512
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Prediction of therapy response of breast cancer patients with machine learning based on clinical data and imaging data derived from breast [F]FDG-PET/MRI.
Kai Jannusch et al. Eur J Nucl Med Mol Imaging 2023
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Air quality and cancer risk in the All of Us Research Program.
Andrew Craver et al. Cancer Causes Control 2023
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Clinical application of convolutional neural network for mass analysis on mammograms.
Lin Li et al. Quant Imaging Med Surg 2023 13(12) 8413-8422
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Validating racial and ethnic non-bias of artificial intelligence decision support for diagnostic breast ultrasound evaluation.
Clara Koo et al. J Med Imaging (Bellingham) 2023 10(6) 061108
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Application of artificial intelligence in ultrasound imaging for predicting lymph node metastasis in breast cancer: A meta-analysis.
Minghui Wang et al. Clin Imaging 2023 106110048
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Ultrasound Radiomics Features to Identify Patients With Triple-Negative Breast Cancer: A Retrospective, Single-Center Study.
Lie Cai et al. J Ultrasound Med 2023
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Nomogram Based on Super-Resolution Ultrasound Images Outperforms in Predicting Benign and Malignant Breast Lesions.
Liu Yang et al. Breast Cancer (Dove Med Press) 2023 15867-878
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External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population.
Olasubomi J Omoleye et al. Radiol Artif Intell 2023 5(6) e220299
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Usefulness of machine learning and deep learning approaches in screening and early detection of breast cancer.
Mohsen Ghorbian et al. Heliyon 2023 9(12) e22427
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Analysis of computational intelligence approaches for predicting disease severity in humans: Challenges and research guidelines.
Geetha Narasimhan et al. J Educ Health Promot 2023 12334
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Artificial Intelligence for the Management of Breast Cancer: An Overview.
Kapil Kumar et al. Curr Drug Discov Technol 2023
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Machine learning improves prediction of clinical outcomes for invasive breast cancers.
et al. Nat Med 2023
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A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer.
Mohamed Amgad et al. Nat Med 2023
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Page last reviewed:
Feb 1, 2024
Page last updated:
May 02, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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