☆ 4.6 Review

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review

CANCERS (2023)

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Article Computer Science, Artificial Intelligence

Ensemble deep learning system for early breast cancer detection

Asmaa A. Hekal et al.

Summary: This paper presents an ensemble deep learning system for early detection of breast cancer, which processes only the suspected nodule regions and achieves better performance in detecting small size nodules. The system consists of four transfer learning convolutional neural networks and binary support vector machines, and the proposed ensemble fusion scheme improves the accuracy of detection and classification.

EVOLUTIONARY INTELLIGENCE (2023)

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Article Radiology, Nuclear Medicine & Medical Imaging

The Role of 68Ga-FAPI PET/CT in Detection of Metastatic Lobular Breast Cancer

Yael Eshet et al.

Summary: This study aimed to assess the feasibility of using Ga-68-fibroblast activation protein inhibitor (FAPI) PET/CT for detecting metastatic disease in patients with non-F-18-FDG-avid invasive lobular breast cancer (ILC). The results showed that FAPI PET/CT was more accurate than CT in detecting metastatic lesions in ILC.

CLINICAL NUCLEAR MEDICINE (2023)

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Proceedings Paper Computer Science, Artificial Intelligence

Diabetic Retinopathy Detection Using 3D OCT Features

Ahmed Sharafeldeen et al.

Summary: This study focuses on developing a computer-assisted diagnostic system that uses 3D optical coherence tomography images to detect diabetic retinopathy. The system separates the retinal layers, computes two 3D characteristics, and performs classification using neural networks. Experimental results validate the system's benefits and potential for detecting diabetic retinopathy.

2023 IEEE 20TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, ISBI (2023)

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Article Radiology, Nuclear Medicine & Medical Imaging

Utility of diffusion tensor imaging in differentiating benign from malignant hepatic focal lesions

Gehad A. Saleh et al.

Summary: This study assessed the diagnostic accuracy of diffusion tensor imaging (DTI) in hepatic focal lesions (HFLs) and compared it to diffusion-weighted imaging (DWI). The results showed that MD and FA of DTI are excellent discriminators, superior to ADC measured by DWI, for differentiating malignant and benign HFLs.

EUROPEAN RADIOLOGY (2023)

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Article Radiology, Nuclear Medicine & Medical Imaging

Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes

Jieun Kim et al.

Summary: This study investigated the predictability of breast MRI for pathologic complete response (pCR) by molecular subtype in patients with breast cancer receiving neoadjuvant chemotherapy (NAC) and explored the MRI findings that can mimic residual malignancy. The results showed that the diagnostic accuracy of MRI for predicting pCR differed by molecular subtypes, and subtle residual enhancement observed on MRI after NAC was associated with false-negative findings.

EUROPEAN RADIOLOGY (2022)

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Article Computer Science, Artificial Intelligence

A machine learning-based approach for the segmentation and classification of malignant cells in breast cytology images using gray level co-occurrence matrix (GLCM) and support vector machine (SVM)

Sana Ullah Khan et al.

Summary: In this article, a machine learning-based approach is proposed for automatic segmentation and classification of malignant cells in breast cytology images, achieving high accuracy of 96.3% through experiments.

NEURAL COMPUTING & APPLICATIONS (2022)

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Article Radiology, Nuclear Medicine & Medical Imaging

Texture and shape analysis of diffusion-weighted imaging for thyroid nodules classification using machine learning

Ahmed Sharafeldeen et al.

Summary: This study aimed to investigate the fusion of features from different MRI imaging modalities to improve the diagnostic accuracy of thyroid nodules classification. By incorporating morphological, textural, and functional imaging features using an artificial neural network, a high accuracy rate of 95.5% was achieved.

MEDICAL PHYSICS (2022)

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Article Oncology

Automatic Segmentation of Metastatic Breast Cancer Lesions on 18F-FDG PET/CT Longitudinal Acquisitions for Treatment Response Assessment

Noemie Moreau et al.

Summary: This study developed two deep learning models for automatic segmentation of metastatic breast cancer lesions and evaluated their potential to determine treatment response through the computation of four imaging biomarkers. The results demonstrated that automatic segmentation can successfully compute these biomarkers, which can be used to determine patients' treatment response.

CANCERS (2022)

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Article Medicine, General & Internal

A Novel Computer-Aided Diagnostic System for Early Detection of Diabetic Retinopathy Using 3D-OCT Higher-Order Spatial Appearance Model

Mohamed Elsharkawy et al.

Summary: In this study, an OCT-based CAD method is proposed for early diagnosis of DR. The method automatically segments retinal layers and extracts texture features for DR diagnosis, and uses ANN for layer-wise classification and majority voting for global diagnosis. The results demonstrate high accuracy using different validation techniques and metrics. Compared to deep learning networks, this method shows promise for early diagnosis of DR.

DIAGNOSTICS (2022)

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Article Radiology, Nuclear Medicine & Medical Imaging

Microwave Imaging in Breast Cancer - Results from the First-In-Human Clinical Investigation of the Wavelia System

Brian M. Moloney et al.

Summary: This study evaluated the clinical application of a low-power electromagnetic wave microwave breast imaging (MBI) system. The results showed that the MBI system was able to detect and localize the majority of breast lesions, including benign lesions and breast cancer. Patients reported a positive experience with the system, and no device-related adverse events were recorded. This study suggests that the MBI system has the potential to serve as a noninvasive, non-ionizing, and painless adjunct to breast cancer diagnosis.

ACADEMIC RADIOLOGY (2022)

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Article Engineering, Biomedical

Automated diagnosis of breast cancer using multi-modal datasets: A deep convolution neural network based approach

Debendra Muduli et al.

Summary: This paper introduces a deep convolutional neural network model for automated breast cancer classification, which outperforms recent state-of-the-art schemes on different datasets, indicating its excellence in accuracy and performance.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2022)

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Editorial Material Radiology, Nuclear Medicine & Medical Imaging

Uncommon Metastases From Occult Breast Cancer Revealed by 18F-FDG and 68Ga-FAPI PET/CT

Weizhi Xu et al.

CLINICAL NUCLEAR MEDICINE (2022)

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Review Pathology

Sentinel lymph node assessment in breast cancer-an update on current recommendations

Gabor Cserni et al.

Summary: This review discusses the background and trends of SLNB, as well as European national recommendations and divergent daily practices in pathology departments. It also highlights the challenges in classifying residual nodal involvement into TNM categories in the post-neoadjuvant setting and summarizes the neoadjuvant therapy-related aspects of SLNB.

VIRCHOWS ARCHIV (2022)

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Article Chemistry, Multidisciplinary

Segmentation of Infant Brain Using Nonnegative Matrix Factorization

Norah Saleh Alghamdi et al.

Summary: This study presents an automated framework for segmenting infants' brains from MRI using features from diffusion tensor imaging. The framework combines visual appearance, shape, and spatial homogeneity modeling to accurately segment different structures of an infant's brain at the isointense age. Promising results are achieved in terms of accuracy, as demonstrated by quantitative and visual assessments.

APPLIED SCIENCES-BASEL (2022)

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Article Engineering, Multidisciplinary

New Sequential and Parallel Support Vector Machine with Grey Wolf Optimizer for Breast Cancer Diagnosis

Elsayed Badr et al.

Summary: The study presents a novel approach to improve breast cancer diagnosis accuracy, including enhancing support vector machine performance, introducing new scaling techniques, and utilizing parallel techniques to enhance efficiency.

ALEXANDRIA ENGINEERING JOURNAL (2022)

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Article Oncology

How AI Can Help in the Diagnostic Dilemma of Pulmonary Nodules

Dalia Fahmy et al.

Summary: This manuscript discusses the applications of artificial intelligence (AI) in lung segmentation, pulmonary nodule segmentation, and classification. It highlights the importance of early detection of pulmonary nodules for lung cancer treatment and saving lives, and how AI technology can improve diagnostic accuracy.

CANCERS (2022)

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Article Medicine, General & Internal

The Role of 3D CT Imaging in the Accurate Diagnosis of Lung Function in Coronavirus Patients

Ibrahim Shawky Farahat et al.

Summary: The paper presents a method of grading COVID-19 using an automatic computer-aided diagnostic system. This system analyzes chest CT images to segment and mark lung regions. After training and testing, the system demonstrates the ability to accurately grade COVID-19 lesions.

DIAGNOSTICS (2022)

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Article Oncology

Breast Cancer, Version 3.2022

William J. Gradishar et al.

Summary: This article discusses the complex therapeutic options for patients with noninvasive or invasive breast cancer, as well as the recommendations provided by the NCCN Clinical Practice Guidelines for Breast Cancer. It focuses on the overall management of ductal carcinoma in situ and the workup and locoregional management of early stage invasive breast cancer.

JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK (2022)

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Review Radiology, Nuclear Medicine & Medical Imaging

Contrast-enhanced Mammography versus Contrast-enhanced Breast MRI: A Systematic Review and Meta-Analysis

Nina Potsch et al.

Summary: This study compared the performance of contrast-enhanced mammography and contrast-enhanced MRI in detecting breast cancer, and found that contrast-enhanced MRI had better sensitivity and negative likelihood ratios, with higher pretest probabilities to rule out malignancy compared to contrast-enhanced mammography.

RADIOLOGY (2022)

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Article Pharmacology & Pharmacy

Effect of concomitant use of pitavastatin with neoadjuvant chemotherapy protocols in breast cancer patients: A randomized controlled clinical trial

Samar A. Dewidar et al.

Summary: This study evaluated the efficacy of concomitant use of pitavastatin with neoadjuvant chemotherapy protocols in patients with breast cancer. The results showed that patients in the pitavastatin group had significantly reduced tumor size, decreased cyclin D1 levels, and increased caspase-3 levels. Subgroup analysis also revealed that HER2-positive patients had a better response to pitavastatin treatment.

SAUDI PHARMACEUTICAL JOURNAL (2022)

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Article Oncology

Machine Learning Models and Multiparametric Magnetic Resonance Imaging for the Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer

Carmen Herrero Vicent et al.

Summary: This study aimed to evaluate whether imaging features (perfusion/diffusion imaging biomarkers + radiomic features) extracted from pre-treatment multiparametric MRIs can predict pCR to NAC, alone or in combination with clinical data. The results showed that a combination of imaging features and clinical variables improved pCR prediction compared to models only including imaging or clinical data, with an accuracy of 91.5%.

CANCERS (2022)

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Article Oncology

Comparison of Diagnostic Efficacy of [68Ga]Ga-FAPI-04 and [18F]FDG PET/CT for Staging and Restaging of Gastric Cancer

Shumao Zhang et al.

Summary: This study compared the diagnostic efficacy of [Ga-68]Ga-FAPI-04 PET/CT and [F-18]-FDG PET/CT for gastric cancer, showing that [Ga-68]Ga-FAPI-04 PET/CT had higher sensitivity for detecting primary tumors, lymph nodes, and distant metastases. It also provided more accurate information for tumor staging and restaging in gastric cancer.

FRONTIERS IN ONCOLOGY (2022)

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Article Chemistry, Analytical

Detection of Diabetic Retinopathy Using Extracted 3D Features from OCT Images

Mahmoud Elgafi et al.

Summary: This study presents a three-step system for detecting diabetic retinopathy using optical coherence tomography (OCT). Experimental results show that the proposed system outperforms related methods and achieves a high accuracy rate.

SENSORS (2022)

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Article Chemistry, Multidisciplinary

A Computer-Aided Diagnostic System for Diabetic Retinopathy Based on Local and Global Extracted Features

Sayed Haggag et al.

Summary: This paper presents a novel deep learning system for the detection and diagnosis of diabetic retinopathy using optical coherence tomography (OCT) images. Experimental results show that the system performs well compared to other methods and the use of fused images significantly improves the diagnostic performance.

APPLIED SCIENCES-BASEL (2022)

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Proceedings Paper Computer Science, Artificial Intelligence

Thyroid Cancer Diagnostic System using Magnetic Resonance Imaging

A. Sharafeldeen et al.

Summary: The study proposes a computer-aided diagnosis system using MRI scans to detect the malignancy of thyroid nodules. By extracting specific features and applying neural networks for diagnosis, the system achieves highly accurate results in classifying thyroid nodules.

2022 26TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) (2022)

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Proceedings Paper Engineering, Biomedical

DIABETIC RETINOPATHY DIAGNOSTIC CAD SYSTEM USING 3D-OCT HIGHER ORDER SPATIAL APPEARANCE MODEL

Mohamed Elsharkawy et al.

Summary: A new Computer-Aided Diagnosis method based on Optical Coherence Tomography scans is introduced for early detection of Diabetic Retinopathy. The system segments retinal layers, extracts texture features, and performs layer-by-layer classification, ultimately achieving a global subject diagnosis.

2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022) (2022)

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Article Oncology

FDG-PET/CT in high-risk primary breast cancer-a prospective study of stage migration and clinical impact

Marianne Vogsen et al.

Summary: The study showed that FDG-PET/CT had a significant impact on staging and treatment changes in women with high-risk primary breast cancer, with incidental findings also considered clinically relevant.

BREAST CANCER RESEARCH AND TREATMENT (2021)

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Review Radiology, Nuclear Medicine & Medical Imaging

Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems

Mohammad Eghtedari et al.

Summary: BI-RADS has evolved into a robust structured reporting platform and comprehensive quality assurance tool for mammography, ultrasound, and MRI, with international impact through six language translations. The 5th edition focuses on harmonization of terms across modalities and aims to continue evolving for emerging breast imaging techniques. Areas for improvement include common findings lacking descriptors and clarification of the proper use of category 3.

AMERICAN JOURNAL OF ROENTGENOLOGY (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Contrast-enhanced mammography: past, present, and future

Julie Sogani et al.

Summary: Contrast-enhanced mammography (CEM) combines conventional mammography with iodinated contrast material to improve cancer detection. CEM has comparable performance to breast MRI and can be useful for various indications in clinical practice.

CLINICAL IMAGING (2021)

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Article Engineering, Biomedical

Automatic classification of breast cancer histopathological images based on deep feature fusion and enhanced routing

Pin Wang et al.

Summary: The paper proposes a method for breast cancer histopathological image classification based on deep feature fusion and enhanced routing. The method was tested on the BreaKHis dataset, showing efficient performance for breast cancer classification in clinical settings.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Review Oncology

A comprehensive literature review of patient-reported outcome measures (PROMs) among common breast reconstruction options: What types of breast reconstruction score well?

Sydney Char et al.

Summary: This study aimed to examine the impact of breast reconstruction surgeries on patient satisfaction, with results showing that oncoplastic breast surgery was the most preferred reconstructive modality. Autologous was favored over implant-based reconstruction, while nipple-sparing was preferred over skin-sparing mastectomy.

BREAST JOURNAL (2021)

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Article Oncology

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Hyuna Sung et al.

Summary: The global cancer burden in 2020 saw an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths. Female breast cancer surpassed lung cancer as the most commonly diagnosed cancer, while lung cancer remained the leading cause of cancer death. These trends are expected to rise in 2040, with transitioning countries experiencing a larger increase compared to transitioned countries due to demographic changes and risk factors associated with globalization and a growing economy. Efforts to improve cancer prevention measures and provision of cancer care in transitioning countries will be crucial for global cancer control.

CA-A CANCER JOURNAL FOR CLINICIANS (2021)

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Article Oncology

Neoadjuvant Chemotherapy, Endocrine Therapy, and Targeted Therapy for Breast Cancer: ASCO Guideline

Larissa A. Korde et al.

Summary: The guideline recommendations for neoadjuvant therapy for breast cancer suggest that patients should be managed by multidisciplinary teams and that appropriate candidates include those with inflammatory breast cancer or residual disease that may prompt a change in therapy.

JOURNAL OF CLINICAL ONCOLOGY (2021)

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Article Multidisciplinary Sciences

Precise higher-order reflectivity and morphology models for early diagnosis of diabetic retinopathy using OCT images

A. Sharafeldeen et al.

Summary: This study presents a novel CAD system for early detection of DR using OCT B-scans, utilizing a segmentation approach that automatically separates retinal layers and extracts high-order morphological and reflectivity markers to improve diagnosis accuracy. The system achieved high performance in diagnosing DR through the fusion of different markers and machine learning techniques.

SCIENTIFIC REPORTS (2021)

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Review Oncology

Combination of Modern Radiotherapy and New Targeted Treatments for Breast Cancer Management

Arnaud Beddok et al.

Summary: The combination of the most commonly used or under development targeted treatments with radiation therapy appears to be feasible for breast cancer patients, but further validation is needed through prospective randomized studies.

CANCERS (2021)

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Article Engineering, Electrical & Electronic

Automated early breast cancer detection and classification system

Asmaa A. Hekal et al.

Summary: Early detection of breast cancer is crucial for reducing mortality rate. This study introduces a new CAD system using deep convolutional neural networks and support vector machine classifier to classify mammogram tumors as benign or malignant, achieving high accuracy in the classification process.

SIGNAL IMAGE AND VIDEO PROCESSING (2021)

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Article Medicine, General & Internal

SAFE: A Novel Microwave Imaging System Design for Breast Cancer Screening and Early Detection-Clinical Evaluation

Aleksandar Janjic et al.

Summary: SAFE is a novel microwave imaging device for breast cancer screening and early detection, using harmless electromagnetic waves without the need for X-rays. Initial results show promising concordance with clinical reports, encouraging further studies on its effectiveness. Breast size was found to influence sensitivity rates, with smaller breasts having lower sensitivity compared to larger ones.

DIAGNOSTICS (2021)

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Review Radiology, Nuclear Medicine & Medical Imaging

Breast cancer: initial workup and staging with FDG PET/CT

David Groheux et al.

Summary: FDG-PET/CT is useful for staging patients with breast cancer, starting from clinical stage IIB, regardless of tumor phenotype and grade. It performs better in staging invasive ductal carcinoma, but is also helpful for invasive lobular carcinomas. FDG-PET/CT may be useful for staging in clinical stage IIA, but routine use in this subgroup is not strongly recommended. Staging with FDG-PET/CT offers no added value for patients in clinical stage I.

CLINICAL AND TRANSLATIONAL IMAGING (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Contrast enhanced mammography (CEM) versus magnetic resonance imaging (MRI) for staging of breast cancer: The pro CEM perspective

M. B. Lobbes et al.

Summary: In women with newly diagnosed breast cancer, preoperative staging utilizing contrast-enhanced mammography (CEM) and ultrasound (US) as a single appointment imaging strategy may reduce the need for additional breast MRI. Both CEM and MRI perform equally well for tumor size measurements and detecting breast cancer, but CEM shows slightly better specificity, leading to fewer false positive findings in preoperative staging.

EUROPEAN JOURNAL OF RADIOLOGY (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Imaging Updates to Breast Cancer Lymph Node Management

Hannah L. Chung et al.

Summary: Metastatic lymph node involvement in breast cancer plays a crucial role in determining disease stage and prognosis. Neoadjuvant systemic treatment is increasingly used as initial therapy. Imaging and image-guided interventions are essential for lymph node assessment and treatment decision-making.

RADIOGRAPHICS (2021)

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Article Chemistry, Analytical

Precise Segmentation of COVID-19 Infected Lung from CT Images Based on Adaptive First-Order Appearance Model with Morphological/Anatomical Constraints

Ahmed Sharafeldeen et al.

Summary: A new segmentation technique using a probabilistic model and modified algorithm was proposed to accurately delineate lung structures in CT images, showing promising results in COVID-19 patients' data.

SENSORS (2021)

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Article Multidisciplinary Sciences

Early assessment of lung function in coronavirus patients using invariant markers from chest X-rays images

Mohamed Elsharkawy et al.

Summary: The study aims to develop a CAD system for assessing pulmonary function and mortality risk in COVID-19 patients, utilizing X-ray data and utilizing a MGRF model and neural network for diagnosis. Experimental results indicate the potential value of this system for physicians to objectively evaluate disease severity and predict mortality risk in patients.

SCIENTIFIC REPORTS (2021)

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Article Oncology

Preoperative localization of sentinel lymph node in breast cancer patients by silver wire insertion or liquid charcoal injection guided by CT lymphography

Omar Hamdy et al.

BREAST JOURNAL (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Interobserver variability and likelihood of malignancy for fifth edition BI-RADS MRI descriptors in non-mass breast lesions

Magdalena Lunkiewicz et al.

EUROPEAN RADIOLOGY (2020)

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Review Radiology, Nuclear Medicine & Medical Imaging

Update on Breast Density, Risk Estimation, and Supplemental Screening

Stamatia Destounis et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2020)

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Article Ophthalmology

Automated Diagnosis of Diabetic Retinopathy Using Clinical Biomarkers, Optical Coherence Tomography, and Optical Coherence Tomography Angiography

Harpal Singh Sandhu et al.

AMERICAN JOURNAL OF OPHTHALMOLOGY (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

BI-RADS category 3, 4, and 5 lesions identified at preoperative breast MRI in patients with breast cancer: implications for management

Si Eun Lee et al.

EUROPEAN RADIOLOGY (2020)

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Article Health Care Sciences & Services

Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN)

S. Akila Agnes et al.

JOURNAL OF MEDICAL SYSTEMS (2020)

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Review Oncology

Towards personalized treatment for early stage HER2-positive breast cancer

Kristina Goutsouliak et al.

NATURE REVIEWS CLINICAL ONCOLOGY (2020)

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Article Acoustics

BREAST CANCER CLASSIFICATION IN AUTOMATED BREAST ULTRASOUND USING MULTIVIEW CONVOLUTIONAL NEURAL NETWORK WITH TRANSFER LEARNING

Yi Wang et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2020)

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Review Medicine, General & Internal

Breast Cancer Detection-A Synopsis of Conventional Modalities and the Potential Role of Microwave Imaging

Brian M. Moloney et al.

DIAGNOSTICS (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Outcome of Screening MRI in Premenopausal Women as a Function of the Week of the Menstrual Cycle

Carol H. Lee et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2020)

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Review Oncology

Recent advances in radiotherapy of breast cancer

Jan Haussmann et al.

RADIATION ONCOLOGY (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Cancer Yield and Patterns of Follow-up for BI-RADS Category 3 after Screening Mammography Recall in the National Mammography Database

Wendie A. Berg et al.

RADIOLOGY (2020)

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Review Oncology

Neoadjuvant Treatment for Triple Negative Breast Cancer: Recent Progresses and Challenges

Jin Sun Lee et al.

CANCERS (2020)

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Article Oncology

Ki-67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study

Yanna Zhang et al.

CANCER COMMUNICATIONS (2020)

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Article Oncology

Characteristics and prognosis of 17 special histologic subtypes of invasive breast cancers according to World Health Organization classification: comparative analysis to invasive carcinoma of no special type

Jiyoung Kim et al.

BREAST CANCER RESEARCH AND TREATMENT (2020)

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Review Oncology

Endocrine Therapy in Early Breast Cancer

Katja Krauss et al.

BREAST CARE (2020)

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Review Surgery

Sentinel lymph node biopsy in breast cancer-an updated overview

Omar Hamdy et al.

EUROPEAN SURGERY-ACTA CHIRURGICA AUSTRIACA (2020)

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Article Multidisciplinary Sciences

A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI

Qiyuan Hu et al.

SCIENTIFIC REPORTS (2020)

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Article Computer Science, Information Systems

Breast cancer masses classification using deep convolutional neural networks and transfer learning

Shayma'a A. Hassan et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2020)

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Review Oncology

Contrast-Enhanced Mammography: A Scientific Review

John M. Lewin et al.

JOURNAL OF BREAST IMAGING (2020)

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Review Oncology

Neoadjuvant Chemotherapy for Breast Cancer: Past, Present, and Future

Mariko Asaoka et al.

BREAST CANCER-BASIC AND CLINICAL RESEARCH (2020)

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Article Oncology

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy

Elizabeth J. Sutton et al.

BREAST CANCER RESEARCH (2020)

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Article Mathematical & Computational Biology

Breast cancer classification with reduced feature set using association rules and support vector machine

Abderrahmane Ed-daoudy et al.

NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS (2020)

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The added value of digital breast tomosynthesis in improving diagnostic performance of BI-RADS categorization of mammographically indeterminate breast lesions

Mohammad Abd Alkhalik Basha et al.

INSIGHTS INTO IMAGING (2020)

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Dataset of breast ultrasound images

Walid Al-Dhabyani et al.

DATA IN BRIEF (2020)

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S-Detect characterization of focal breast lesions according to the US BI RADS lexicon: a pictorial essay

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JOURNAL OF ULTRASOUND (2020)

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Review Radiology, Nuclear Medicine & Medical Imaging

The Evolving Role of FDG-PET/CT in the Diagnosis, Staging, and Treatment of Breast Cancer

Koosha Paydary et al.

MOLECULAR IMAGING AND BIOLOGY (2019)

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Review Radiology, Nuclear Medicine & Medical Imaging

Contouring consensus guidelines in breast cancer radiotherapy: Comparison and systematic review of patterns of failure

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Article Radiology, Nuclear Medicine & Medical Imaging

Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients

Amirhessam Tahmassebi et al.

INVESTIGATIVE RADIOLOGY (2019)

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Article Oncology

被撤回的出版物: TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathologic Complete Response to Pertuzumab and Trastuzumab in Breast Cancer (Retracted article. See vol. 39, pg. 2319, 2021)

Roisin M. Connolly et al.

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Article Computer Science, Information Systems

Detection of breast cancer mass using MSER detector and features matching

Shayma'a A. Hassan et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2019)

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Review Radiology, Nuclear Medicine & Medical Imaging

PET/CT for Patients With Breast Cancer: Where Is the Clinical Impact?

Gary A. Ulaner

AMERICAN JOURNAL OF ROENTGENOLOGY (2019)

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Article Computer Science, Artificial Intelligence

Convolutional neural network improvement for breast cancer classification

Fung Fung Ting et al.

EXPERT SYSTEMS WITH APPLICATIONS (2019)

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Article Radiology, Nuclear Medicine & Medical Imaging

68Ga-FAPI PET/CT: Tracer Uptake in 28 Different Kinds of Cancer

Clemens Kratochwil et al.

JOURNAL OF NUCLEAR MEDICINE (2019)

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Editorial Material Oncology

The ESMO clinical practise guidelines for early breast cancer: diagnosis, treatment and follow-up: on the winding road to personalized medicine

S. Loi

ANNALS OF ONCOLOGY (2019)

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Correction Oncology

Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up (vol 30, pg 128, 2019)

F. Cardoso et al.

ANNALS OF ONCOLOGY (2019)

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Article Health Care Sciences & Services

Breast Cancer Diagnosis Using Feature Ensemble Learning Based on Stacked Sparse Autoencoders and Softmax Regression

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Article Oncology

New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)

E. A. Eisenhauer et al.

EUROPEAN JOURNAL OF CANCER (2009)

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An expert system for detection of breast cancer based on association rules and neural network

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EXPERT SYSTEMS WITH APPLICATIONS (2009)

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Strategies for digital mammography interpretation in a clinical patient population

Frank. J. H. M. van den Biggelaar et al.

INTERNATIONAL JOURNAL OF CANCER (2009)

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Monitoring Primary Systemic Therapy of Large and Locally Advanced Breast Cancer by Using Sequential Positron Emission Tomography Imaging With [18F] Fluorodeoxyglucose

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JOURNAL OF CLINICAL ONCOLOGY (2009)

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Article Radiology, Nuclear Medicine & Medical Imaging

Assessment of Interobserver Reproducibility in Quantitative 18F-FDG PET and CT Measurements of Tumor Response to Therapy

Heather A. Jacene et al.

JOURNAL OF NUCLEAR MEDICINE (2009)

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Article Radiology, Nuclear Medicine & Medical Imaging

Standards for PET Image Acquisition and Quantitative Data Analysis

Ronald Boellaard

JOURNAL OF NUCLEAR MEDICINE (2009)

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Article Radiology, Nuclear Medicine & Medical Imaging

Diffusion-weighted MR for Differentiation of Breast Lesions at 3.0 T: How Does Selection of Diffusion Protocols Affect Diagnosis?

Wolfgang Bogner et al.

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Bone metastases in patients with metastatic breast cancer: Morphologic and metabolic monitoring of response to systemic therapy with integrated PET/CT

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RADIOLOGY (2008)

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American society of clinical oncology 2007 update of recommendations for the use of tumor markers in breast cancer

Lyndsay Harris et al.

JOURNAL OF CLINICAL ONCOLOGY (2007)

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Editorial Material Oncology

American Society of Clinical Oncology 2007 Update of Recommendations for the Use of Tumor Markers in Breast Cancer

[Anonymous]

JOURNAL OF ONCOLOGY PRACTICE (2007)

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Breast tomosynthesis: Present considerations and future applications

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RADIOGRAPHICS (2007)

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Monitoring of early response to neoadjuvant chemotherapy in stage II and III breast cancer by [18F]fluorodeoxyglucose positron emission tomography

Caroline Rousseau et al.

JOURNAL OF CLINICAL ONCOLOGY (2006)

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Article Radiology, Nuclear Medicine & Medical Imaging

Concordance of mammographic classifications of microcalcifications in breast cancer diagnosis -: Utility of the Breast Imaging Reporting and Data System (fourth edition)

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CLINICAL IMAGING (2005)

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Article Radiology, Nuclear Medicine & Medical Imaging

Revisiting the mammographic follow-up of BI-RADS category 3 lesions

X Varas et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2002)

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An evolutionary artificial neural networks approach for breast cancer diagnosis

HA Abbass

ARTIFICIAL INTELLIGENCE IN MEDICINE (2002)

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NATURE (2000)

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