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Breast Neoplasms

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A deep learning-based method for the detection and segmentation of breast masses in ultrasound images.

Physics in medicine and biology
Automated detection and segmentation of breast masses in ultrasound images are critical for breast cancer diagnosis, but remain challenging due to limited image quality and complex breast tissues. This study aims to develop a deep learning-based meth...

Impact of Downsampling Size and Interpretation Methods on Diagnostic Accuracy in Deep Learning Model for Breast Cancer Using Digital Breast Tomosynthesis Images.

The Tohoku journal of experimental medicine
While deep learning (DL) models have shown promise in breast cancer diagnosis using digital breast tomosynthesis (DBT) images, the impact of varying matrix sizes and image interpolation methods on diagnostic accuracy remains unclear. Understanding th...

Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the breast tissue. In a few cases, erroneous diagnosis of breast cancer by specialists and unnecessary biopsies can lead to various negative consequences. In ...

Biomarker profiling and integrating heterogeneous models for enhanced multi-grade breast cancer prognostication.

Computer methods and programs in biomedicine
BACKGROUND: Breast cancer remains a leading cause of female mortality worldwide, exacerbated by limited awareness, inadequate screening resources, and treatment options. Accurate and early diagnosis is crucial for improving survival rates and effecti...

Self-organizing maps for exploration and classification of nuclear magnetic resonance spectra for untargeted metabolomics of breast cancer.

Journal of pharmaceutical and biomedical analysis
Metabolomics has emerged as a powerful tool for identifying biomarkers of disease, and nuclear magnetic resonance (NMR) spectroscopy allows for the simultaneous detection of a wide range of metabolites. However, due to complex interactions within met...

Interpretation of Artificial Intelligence Models in Healthcare: A Pictorial Guide for Clinicians.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Artificial intelligence (AI) models can play a more effective role in managing patients with the explosion of digital health records available in the healthcare industry. Machine-learning (ML) and deep-learning (DL) techniques are two methods used to...

Deep learning-enabled high-speed, multi-parameter diffuse optical tomography.

Journal of biomedical optics
SIGNIFICANCE: Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical breast tumor characterization. However, conventional diffuse optical tomography (DOT) image reconstruction algorithms require case-by-case expert tuning and are...

Investigating the effects of artificial intelligence on the personalization of breast cancer management: a systematic study.

BMC cancer
BACKGROUND: Providing appropriate specialized treatment to the right patient at the right time is considered necessary in cancer management. Targeted therapy tailored to the genetic changes of each breast cancer patient is a desirable feature of prec...

Artificial Intelligence-Driven Prediction Revealed CFTR Associated with Therapy Outcome of Breast Cancer: A Feasibility Study.

Oncology
INTRODUCTION: In silico tools capable of predicting the functional consequences of genomic differences between individuals, many of which are AI-driven, have been the most effective over the past two decades for non-synonymous single nucleotide varia...