Oncology/Hematology

Breast Cancer

Latest AI and machine learning research in breast cancer for healthcare professionals.

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Mask-Guided Convolutional Neural Network for Breast Tumor Prognostic Outcome Prediction on 3D DCE-MR Images.

In this proof-of-concept work, we have developed a 3D-CNN architecture that is guided by the tumor m...

Radiomics analysis on CT images for prediction of radiation-induced kidney damage by machine learning models.

INTRODUCTION: We aimed to assess the power of radiomic features based on computed tomography to pred...

PathoNet introduced as a deep neural network backend for evaluation of Ki-67 and tumor-infiltrating lymphocytes in breast cancer.

The nuclear protein Ki-67 and Tumor infiltrating lymphocytes (TILs) have been introduced as prognost...

Oncologic Equipoise Between Robotic and Open Radical Cystectomy.

Our objective was to establish the incidence of positive surgical margins, recurrence patterns, and...

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

The two-dimensional nature of mammography makes estimation of the overall breast density challenging...

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because...

Magnetic tri-bead microrobot assisted near-infrared triggered combined photothermal and chemotherapy of cancer cells.

Magnetic micro/nanorobots attracted much attention in biomedical fields because of their precise mov...

Impact of image compression on deep learning-based mammogram classification.

Image compression is used in several clinical organizations to help address the overhead associated ...

Simulating reference crop evapotranspiration with different climate data inputs using Gaussian exponential model.

Obtaining accurate data on reference crop evapotranspiration (ET) is important for agricultural wate...

Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.

Background Conventional radiologic modalities perform poorly in the radiated rectum and are often un...

An Intuitionistic Fuzzy Clustering Approach for Detection of Abnormal Regions in Mammogram Images.

Breast cancer is one of the leading causes of mortality in the world and it occurs in high frequency...

Radiation therapy dose prediction for left-sided breast cancers using two-dimensional and three-dimensional deep learning models.

PURPOSE: To develop a deep learning model capable of producing clinically acceptable dose distributi...

Radiation dose calculation in 3D heterogeneous media using artificial neural networks.

PURPOSE: External beam radiotherapy (EBRT) treatment planning requires a fast and accurate method of...

CycleGAN for interpretable online EMT compensation.

PURPOSE: Electromagnetic tracking (EMT) can partially replace X-ray guidance in minimally invasive p...

CT based automatic clinical target volume delineation using a dense-fully connected convolution network for cervical Cancer radiation therapy.

BACKGROUND: It is very important to accurately delineate the CTV on the patient's three-dimensional ...

Is Anti-Müllerian Hormone a Marker of Ovarian Reserve in Young Breast Cancer Patients Receiving a GnRH Analog during Chemotherapy?

INTRODUCTION: Anti-Müllerian hormone (AMH) is the most reliable biomarker of ovarian reserve; howeve...

Therapeutic Potentials of Selected Antihypertensive Agents and Their Fixed-Dose Combinations Against Trastuzumab-Mediated Cardiotoxicity.

Trastuzumab () is useful in the clinical management of HER2-positive metastatic breast, gastric, and...

Accurate surface ultraviolet radiation forecasting for clinical applications with deep neural network.

Exposure to appropriate doses of UV radiation provides enormously health and medical treatment benef...

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