AIMC Topic: Breast Neoplasms

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CNN-based deep learning approach for classification of invasive ductal and metastasis types of breast carcinoma.

Cancer medicine
OBJECTIVE: Breast cancer is one of the leading cancer causes among women worldwide. It can be classified as invasive ductal carcinoma (IDC) or metastatic cancer. Early detection of breast cancer is challenging due to the lack of early warning signs. ...

Accuracy of an Artificial Intelligence System for Interval Breast Cancer Detection at Screening Mammography.

Radiology
Background Artificial intelligence (AI) systems can be used to identify interval breast cancers, although the localizations are not always accurate. Purpose To evaluate AI localizations of interval cancers (ICs) on screening mammograms by IC category...

Automated Extraction of Patient-Centered Outcomes After Breast Cancer Treatment: An Open-Source Large Language Model-Based Toolkit.

JCO clinical cancer informatics
PURPOSE: Patient-centered outcomes (PCOs) are pivotal in cancer treatment, as they directly reflect patients' quality of life. Although multiple studies suggest that factors affecting breast cancer-related morbidity and survival are influenced by tre...

A Neural Network-Based Scoring System for Predicting Prognosis and Therapy in Breast Cancer.

Current protocols
Breast cancer is a prevalent malignancy affecting women worldwide. Currently, there are no precise molecular biomarkers with immense potential for accurately predicting breast cancer development, which limits clinical management options. Recent evide...

Development and Validation of a Natural Language Processing Algorithm for Extracting Clinical and Pathological Features of Breast Cancer From Pathology Reports.

JCO clinical cancer informatics
PURPOSE: Electronic health records (EHRs) are valuable information repositories that offer insights for enhancing clinical research on breast cancer (BC) using real-world data. The objective of this study was to develop a natural language processing ...

Insights Into the Patient Experience of Hormone Therapy for Early Breast Cancer Treatment Using Patient Forum Discussions and Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Understanding the real-world experience of patients with early breast cancer (eBC) is imperative for optimizing outcomes and evolving patient care. However, there is a lack of patient-level data, hindering clinical development. This social l...

Integrating single-cell transcriptomics and machine learning to predict breast cancer prognosis: A study based on natural killer cell-related genes.

Journal of cellular and molecular medicine
Breast cancer (BC) is the most commonly diagnosed cancer in women globally. Natural killer (NK) cells play a vital role in tumour immunosurveillance. This study aimed to establish a prognostic model using NK cell-related genes (NKRGs) by integrating ...

[Diagnostic Value of Micropure Imaging Combined with Strain Elastography in Correcting Artificial Intelligence S-Detect Technology for Benign and Malignant Breast Complex Cystic and Solid Masses].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: To explore the diagnostic value of micropure imaging (MI) combined with strain elastography (SE) in correcting artificial intelligence (AI) S-Detect technology for benign and malignant breast complex cystic and solid masses.

A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.

Journal of breast imaging
OBJECTIVE: The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating "silently"...

Breast Cancer Tissue Classification from Multiple Annotators using Chained Deep Learning Approaches.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Breast cancer is one of the principal causes of cancer death worldwide. The biopsy diagnosis is non-trivial, and specialists often disagree on the final diagnosis. Thus, Computer-aided Diagnosis-(CAD) systems favor the efficiency of this process whil...