AIMC Topic: Breast Neoplasms

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Detection of breast cancer using machine learning on time-series diffuse optical transillumination data.

Journal of biomedical optics Nov 11, 2024
SIGNIFICANCE: Optical mammography as a promising tool for cancer diagnosis has largely fallen behind expectations. Modern machine learning (ML) methods offer ways to improve cancer detection in diffuse optical transmission data.
Humans Machine Learning Female Image Interpretation, Computer-Assisted Support Vector Machine Optical Imaging Area Under Curve Transillumination Breast Breast Neoplasms ROC Curve Image Processing, Computer-Assisted
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IoT based healthcare system using fractional dung beetle optimization enabled deep learning for breast cancer classification.

Computational biology and chemistry Nov 10, 2024
Breast cancer classification plays a crucial role in healthcare, especially in the diagnosis and monitoring of patients. Traditional methods for classifying breast cancer based on histopathological images often suffer from limited accuracy, which can...
Coleoptera Humans Female Animals Breast Neoplasms Deep Learning Internet of Things
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Fusing global context with multiscale context for enhanced breast cancer classification.

Scientific reports Nov 9, 2024
Breast cancer is the second most common type of cancer among women. Prompt detection of breast cancer can impede its advancement to more advanced phases, thereby elevating the probability of favorable treatment consequences. Histopathological images ...
Female Breast Neoplasms Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms
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An open codebase for enhancing transparency in deep learning-based breast cancer diagnosis utilizing CBIS-DDSM data.

Scientific reports Nov 9, 2024
Accessible mammography datasets and innovative machine learning techniques are at the forefront of computer-aided breast cancer diagnosis. However, the opacity surrounding private datasets and the unclear methodology behind the selection of subset im...
Humans Software Early Detection of Cancer Mammography Diagnosis, Computer-Assisted Databases, Factual Deep Learning Female Image Processing, Computer-Assisted Breast Neoplasms
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An explainable longitudinal multi-modal fusion model for predicting neoadjuvant therapy response in women with breast cancer.

Nature communications Nov 7, 2024
Multi-modal image analysis using deep learning (DL) lays the foundation for neoadjuvant treatment (NAT) response monitoring. However, existing methods prioritize extracting multi-modal features to enhance predictive performance, with limited consider...
Multimodal Imaging Treatment Outcome Neoadjuvant Therapy Longitudinal Studies Breast Neoplasms Middle Aged Deep Learning Humans Female Aged Adult
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Supporting the care to breast cancer patients with unique needs: Evidence from online community members' responses.

International journal of medical informatics Nov 6, 2024
BACKGROUND: Breast cancer is the most common cancer diagnosed in women globally. Online cancer communities (OCCs) provide platforms for breast cancer patients to connect, share experiences, and support each other. These communities facilitate discuss...
Social Media Humans Natural Language Processing Female Breast Neoplasms Internet Deep Learning Social Support
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Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics.

Scientific reports Nov 6, 2024
The axillary lymph node status remains an important prognostic factor in breast cancer, and nodal staging using sentinel lymph node biopsy (SLNB) is routine. Randomized clinical trials provide evidence supporting de-escalation of axillary surgery and...
Axilla Sentinel Lymph Node Sentinel Lymph Node Biopsy Middle Aged Deep Learning Lymphatic Metastasis Humans Female Aged Adult Breast Neoplasms
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A Deep Learning Model to Predict Breast Implant Texture Types Using Ultrasonography Images: Feasibility Development Study.

JMIR formative research Nov 5, 2024
BACKGROUND: Breast implants, including textured variants, have been widely used in aesthetic and reconstructive mammoplasty. However, the textured type, which is one of the shell texture types of breast implants, has been identified as a possible eti...
Breast Neoplasms Deep Learning Ultrasonography Humans Retrospective Studies Female Feasibility Studies Breast Implants Lymphoma, Large-Cell, Anaplastic
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Combination of Deep Learning Grad-CAM and Radiomics for Automatic Localization and Diagnosis of Architectural Distortion on DBT.

Academic radiology Nov 3, 2024
RATIONALE AND OBJECTIVES: Detection and diagnosis of architectural distortion (AD) on digital breast tomosynthesis (DBT) is challenging. This study applied artificial intelligence (AI) using deep learning (DL) algorithms to detect AD, followed by rad...
Radiographic Image Interpretation, Computer-Assisted Middle Aged Deep Learning Female Humans Mammography Algorithms Aged Retrospective Studies Sensitivity and Specificity Adult Breast Neoplasms Radiomics
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NSSC: a neuro-symbolic AI system for enhancing accuracy of named entity recognition and linking from oncologic clinical notes.

Medical & biological engineering & computing Nov 1, 2024
Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting insights across cancer research, patient care, clinical decision-making, and treatment optimization. We present the Neuro-Symbolic System for Cancer ...
Humans Neural Networks, Computer Breast Neoplasms Artificial Intelligence Neoplasms Natural Language Processing Electronic Health Records Unified Medical Language System Female
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