Breast Cancer

[A Patient with Multiple Colorectal Liver Metastases for Whom Partial Splenic Embolization Contributed Extremely to Maintain Multidisciplinary Treatment].

After approximately 2.5 years of chemotherapy at the referred hospital, a 69-year-old man with doubl...

[A Case of Disseminated Carcinomatosis of the Bone Marrow Developing 15 Months after Gastrectomy].

The patient was a 60-year-old man who underwent distal gastrectomy for gastric cancer. The pathologi...

A future of automated image contouring with machine learning in radiation therapy.

Automated image contouring is showing improvements in efficiency for a number of clinical tasks in r...

A convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients.

The purpose of the study was to compare a 3D convolutional neural network (CNN) with the conventiona...

Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study.

Positron emission tomography (PET) imaging is an effective tool used in determining disease stage an...

Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.

We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemother...

The Role of Generative Adversarial Networks in Radiation Reduction and Artifact Correction in Medical Imaging.

Adversarial networks were developed to complete powerful image-processing tasks on the basis of exam...

Using Artificial Intelligence to Improve the Quality and Safety of Radiation Therapy.

Within artificial intelligence, machine learning (ML) efforts in radiation oncology have augmented t...

Lens Identification to Prevent Radiation-Induced Cataracts Using Convolutional Neural Networks.

Exposure of the lenses to direct ionizing radiation during computed tomography (CT) examinations pre...

Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm.

Radiological measurements are reported in free text reports, and it is challenging to extract such m...

Deep Learning Based Dosimetry Evaluation at Organs-at-Risk in Esophageal Radiation Treatment Planning.

Rapid esophageal radiation treatment planning is often obstructed by manually adjusting optimization...

Restoration of Full Data from Sparse Data in Low-Dose Chest Digital Tomosynthesis Using Deep Convolutional Neural Networks.

Chest digital tomosynthesis (CDT) provides more limited image information required for diagnosis whe...

A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care.

Background uPA and PAI-1 are breast cancer biomarkers that evaluate the benefit of chemotherapy (CT)...

Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting.

IMPORTANCE: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncolo...

Predicting Breast Cancer Molecular Subtype with MRI Dataset Utilizing Convolutional Neural Network Algorithm.

To develop a convolutional neural network (CNN) algorithm that can predict the molecular subtype of ...

Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers.

Applying state-of-the-art machine learning techniques to medical images requires a thorough selectio...

Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer.

Breast cancer prognosis and administration of therapies are aided by knowledge of hormonal and HER2 ...

MR-based treatment planning in radiation therapy using a deep learning approach.

PURPOSE: To develop and evaluate the feasibility of deep learning approaches for MR-based treatment ...

Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models ...

Radiomics - Using Artificial Intelligence in the Quest towards Personalised Radiation Treatment.

Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.

PURPOSE: The aim of this study was to assess the potential of machine learning with multiparametric ...