Cardiovascular

Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre- and posttreatment computed tomography scans of 123 patients (cancers, 129; pre- and posttreatment cancer pairs, 158) undergoing chemotherapy were col...

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 planning (deepMTP) in brain tumor radiation therapy.

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 magnetic resonance imaging (mpMRI) for the early p...

Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning.

Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the...

Radiomics with artificial intelligence for precision medicine in radiation therapy.

Recently, the concept of radiomics has emerged from radiation oncology. It is a novel approach for solving the issues of precision medicine and how it...

Constructing a Risk Prediction Model for Lung Cancer Recurrence by Using Gene Function Clustering and Machine Learning.

OBJECTIVE: A significant proportion of patients with early non-small cell lung cancer (NSCLC) can be cured by surgery. The distant metastasis of tumor...

Iterative image reconstruction for sparse-view CT via total variation regularization and dictionary learning.

Recently, low-dose computed tomography (CT) has become highly desirable due to the increasing attention paid to the potential risks of excessive radia...

Anticancer Activity of Polyisoprenoids from Blume. in WiDr Cells.

Colorectal cancer is the third most common cancer world wide and has been occurred more in developing regions. The use of conventional chemotherapy ag...

[Nephrotoxicity of a Short Hydration Method for the Cisplatin Regimen in Patients with Gastric Cancer].

BACKGROUND: S-1 plus cisplatin(CDDP)has been a key regimen for advanced gastric cancer treatment. However, CDDP confers dose-limiting nephrotoxicity, ...

[A Case of Laparoscopic Resection for Locally Advanced Primary Rectal Cancer after Neoadjuvant Chemotherapy].

We treateda 70-year-oldfemale patient with locally advancedrectal cancer accompaniedby metastases to other organs. Three courses of S-1 plus oxaliplat...

[A Surgical Case of AFP-Producing Gastric Cancer Discovered by Rupture of Liver Metastatic Lesion].

A 57-year-old man visited our hospital with right hypochondralgia. Abdominal contrast CT showed a 10 cm sized mass in S6-7of the liver and abdominal h...

Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective.

Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine cl...

Degradation of textile dyes Remazol Yellow Gold and reactive Turquoise: optimization, toxicity and modeling by artificial neural networks.

In this work, the degradation of Remazol Yellow Gold RNL-150% and Reactive Turquoise Q-G125 were investigated using AOP: photolysis, UV/HO, Fenton and...

Automatic Delineation of the Clinical Target Volume in Rectal Cancer for Radiation Therapy using Three-dimensional Fully Convolutional Neural Networks.

Accurate, robust, and fast delineation of the clinical target volume (CTV) for the use in radiotherapy of rectal cancer (RC) is highly sought-after. C...

A Fully Convolutional Deep Neural Network for Lung Tumor Boundary Tracking in MRI.

Delineation of lung tumor from adjacent tissue from a series of magnetic resonance images (MRI) poses many difficulties due to the image similarities ...

Feature specific quantile normalization enables cross-platform classification of molecular subtypes using gene expression data.

MOTIVATION: Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profiling, have provided insight into disease pathogenesis...

3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network.

Low-dose computed tomography (LDCT) has attracted major attention in the medical imaging field, since CT-associated X-ray radiation carries health ris...

Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning.

This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a d...

MRI to MGMT: predicting methylation status in glioblastoma patients using convolutional recurrent neural networks.

Glioblastoma Multiforme (GBM), a malignant brain tumor, is among the most lethal of all cancers. Temozolomide is the primary chemotherapy treatment fo...

Predicting Clinical Outcomes in Colorectal Cancer Using Machine Learning.

Using gene markers and other patient features to predict clinical outcomes plays a vital role in enhancing clinical decision making and improving prog...