Lung Cancer

Is Robotic Complete Mesocolic Excision Feasible for Transverse Colon Cancer?

Laparoscopic complete mesocolic excision (CME) for transverse colon cancer is technically challenging. Robotic technology has been developed to reduce technical limitations of laparoscopy. Yet, no data are available on the role of robotic approach for CME of transverse colon cancer. The aim of this study is to evaluate the feasibility and short-term outcomes of robotic CME in this subset of colon...

MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network.

PURPOSE: This work aims to facilitate a fast magnetic resonance (MR)-only workflow for radiation therapy of intracranial tumors. Here, we evaluate whether synthetic computed tomography (sCT) images generated with a dilated convolutional neural network (CNN) enable accurate MR-based dose calculations in the brain.

Designing Anticancer Peptides by Constructive Machine Learning.

Constructive (generative) machine learning enables the automated generation of novel chemical structures without the need for explicit molecular desig...

Machine learning identifies a core gene set predictive of acquired resistance to EGFR tyrosine kinase inhibitor.

PURPOSE: Acquired resistance (AR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) is a major issue worldwide, for both pati...

Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.

PURPOSE: Treatment effect or radiation necrosis after stereotactic radiosurgery (SRS) for brain metastases is a common phenomenon often indistinguisha...

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decrease...

Robotic Hybrid Approach for an Anterior Pancoast Tumor in a Severely Obese Patient.

Several different surgical approaches to anterior Pancoast tumors have been proposed. The osteomuscular-sparing transmanubrial approach allows optimal...

A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.

Heart motion tracking for radiation therapy treatment planning can result in effective motion management strategies to minimize radiation-induced card...

A survey on Barrett's esophagus analysis using machine learning.

This work presents a systematic review concerning recent studies and technologies of machine learning for Barrett's esophagus (BE) diagnosis and treat...

Flexible robotic catheters in the visceral segment of the aorta: advantages and limitations.

Flexible robotic catheters are an emerging technology which provide an elegant solution to the challenges of conventional endovascular intervention. O...

Using Big Data Analytics to Advance Precision Radiation Oncology.

Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of g...

Machine Learning on a Genome-wide Association Study to Predict Late Genitourinary Toxicity After Prostate Radiation Therapy.

PURPOSE: Late genitourinary (GU) toxicity after radiation therapy limits the quality of life of prostate cancer survivors; however, efforts to explain...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The ...

Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology.

PURPOSE: Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great potential to generate hypotheses for cancer treat...

A method of gene expression data transfer from cell lines to cancer patients for machine-learning prediction of drug efficiency.

Personalized medicine implies that distinct treatment methods are prescribed to individual patients according several features that may be obtained fr...

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning.

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic...

A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy.

With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, b...

Outcomes and toxicity from a prospective study of moderately hypofractionated radiation therapy for prostate cancer.

PURPOSE: The purpose of this study is to report the long-term outcomes and toxicity results of a prospective trial of moderately hypofractionated, ima...

Drug eluting stents are superior to bare metal stents to reduce clinical outcome and stent-related complications in CKD patients, a systematic review, meta-analysis and network meta-analysis.

Aims To compare clinical outcome in Chronic kidney disease (CKD) patients receiving coronary stents according to stent type BMS versus DES and 1st gen...

Overexpression of EMMPRIN is associated with lymph node metastasis and advanced stage of non-small cell lung cancer: a retrospective study.

BACKGROUND: Previous studies show that overexpression of EMMPRIN involved in the malignant biological behavior of tumors. This investigation was to di...