AIMC Topic: Breast Neoplasms

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Enhancing the prediction of IDC breast cancer staging from gene expression profiles using hybrid feature selection methods and deep learning architecture.

Medical & biological engineering & computing
Prediction of the stage of cancer plays an important role in planning the course of treatment and has been largely reliant on imaging tools which do not capture molecular events that cause cancer progression. Gene-expression data-based analyses are a...

FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction.

IEEE transactions on medical imaging
Near-infrared diffuse optical tomography (DOT) is a promising functional modality for breast cancer imaging; however, the clinical translation of DOT is hampered by technical limitations. Specifically, conventional finite element method (FEM)-based o...

Hardware deployment of deep learning model for classification of breast carcinoma from digital mammogram images.

Medical & biological engineering & computing
Cancer is an illness that instils fear in many individuals throughout the world due to its lethal nature. However, in most situations, cancer may be cured if detected early and treated properly. Computer-aided diagnosis is gaining traction because it...

ExpHBA Deep-IoT: Exponential Honey Badger Optimized Deep Learning For Breast Cancer Detection in IoT Healthcare System.

Journal of digital imaging
Breast cancer (BC) is the most widely found disease among women in the world. The early detection of BC can frequently lessen the mortality rate as well as progress the probability of providing proper treatment. Hence, this paper focuses on devising ...

Deep learning-based multiomics integration model for predicting axillary lymph node metastasis in breast cancer.

Future oncology (London, England)
To develop a deep learning-based multiomics integration model. Five types of omics data (mRNA, DNA methylation, miRNA, copy number variation and protein expression) were used to build a deep learning-based multiomics integration model a deep neura...

Deep learning model for predicting the presence of stromal invasion of breast cancer on digital breast tomosynthesis.

Radiological physics and technology
To develop a deep learning (DL)-based algorithm to predict the presence of stromal invasion in breast cancer using digital breast tomosynthesis (DBT). Our institutional review board approved this retrospective study and waived the requirement for inf...

Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers.

EBioMedicine
BACKGROUND: For patients with early-stage breast cancers, neoadjuvant treatment is recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish between luminal and non-luminal cancers at early stages will facilitate treatmen...

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets.

Analytical chemistry
Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typica...