Breast Cancer

Robot-assisted Nipple-sparing Mastectomy with Immediate Breast Reconstruction: An Initial Experience.

Seeking smaller and indistinct incisions, physicians have attempted endoscopic breast surgery in breast cancer patients. Unfortunately, there are some limitations in the range of movement and visualization of the operation field. Potentially addressing these limitations, we investigated the outcomes of gas and gasless robot-assisted nipple-sparing mastectomy (RANSM) with immediate breast reconstru...

Label-Free Estimation of Therapeutic Efficacy on 3D Cancer Spheres Using Convolutional Neural Network Image Analysis.

Despite recent advances in cancer treatment, developing better therapeutic reagents remains an essential task for oncologists. To accurately characterize drug efficacy, 3D cell culture holds great promise as opposed to conventional 2D monolayer culture. Due to the advantages of cell manipulation in high-throughput, various microfluidic platforms have been developed for drug screening with 3D model...

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships betwe...

Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.

INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall survival (OS) for patients with locally advanced no...

Preparing for Artificial Intelligence: Systems-Level Implications for the Medical Imaging and Radiation Therapy Professions.

Innovations in artificial intelligence (AI) are driving a new industrial revolution, and as a result, the medical radiation sciences is experiencing t...

A Machine Learning-Based Prediction Platform for P-Glycoprotein Modulators and Its Validation by Molecular Docking.

P-glycoprotein (P-gp) is an important determinant of multidrug resistance (MDR) because its overexpression is associated with increased efflux of vari...

[Basis and perspectives of artificial intelligence in radiation therapy].

Artificial intelligence is a highly polysemic term. In computer science, with the objective of being able to solve totally new problems in new context...

A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation.

In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumor target delineation and treatment delivery, thus ...

Artificial intelligence applications for pediatric oncology imaging.

Machine learning algorithms can help to improve the accuracy and efficiency of cancer diagnosis, selection of personalized therapies and prediction of...

Outpatient Anesthesia Facilitates Stereotactic Body Radiation Therapy for Early Stage Lung Cancer Patients With Advanced Cognitive Impairments.

PURPOSE: To report on the use of outpatient anesthesia (OPA) facilitating delivery of stereotactic body radiation therapy (SBRT) in patients with seve...

Artificial Intelligence and the Medical Radiation Profession: How Our Advocacy Must Inform Future Practice.

There is no escaping the fact that academics are devoting unrelenting attention to the impact artificial intelligence will have on health care. Radiol...

Two stage residual CNN for texture denoising and structure enhancement on low dose CT image.

BACKGROUND AND OBJECTIVE: X-ray computed tomography (CT) plays an important role in modern medical science. Human health problems caused by CT radiati...

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200000 exams (over 1000...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ultrasound has been proposed to obtain real-time v...

[Prediction of chemotherapy response in primary osteosarcoma using the machine learning technique on radiomic data].

INTRODUCTION: Osteosarcoma is the most common malignant bone tumor before 25 years of age. Response to neoadjuvant chemotherapy determines continuatio...

Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning.

Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance...

Detection of Hemodynamically Significant Coronary Stenosis: CT Myocardial Perfusion versus Machine Learning CT Fractional Flow Reserve.

Background Direct intraindividual comparison of dynamic CT myocardial perfusion imaging (MPI) and machine learning (ML)-based CT fractional flow reser...

Single patient convolutional neural networks for real-time MR reconstruction: a proof of concept application in lung tumor segmentation for adaptive radiotherapy.

Investigate 3D (spatial and temporal) convolutional neural networks (CNNs) for real-time on-the-fly magnetic resonance imaging (MRI) reconstruction. I...

How Much Was the Elective Lymph Node Region Covered in Involved-Field Radiation Therapy for Locally Advanced Pancreatic Cancer? Evaluation of Overlap Between Gross Target Volume and Celiac Artery-Superior Mesenteric Artery Lymph Node Regions.

PURPOSE: The purpose of this study was to investigate the overlaps between gross target volume (GTV) and the celiac artery (CA) and superior mesenteri...

Artificial Intelligence in Radiation Oncology.

The integration of artificial intelligence in the radiation oncologist's workflow has multiple applications and significant potential. From the initia...