Breast Cancer

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 ti...

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 developin...

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 attent...

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...

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 s...

[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...

[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...

[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. Ho...

Predicting Emergency Visits and Hospital Admissions During Radiation and Chemoradiation: An Internally Validated Pretreatment Machine Learning Algorithm.

PURPOSE: Patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) may require emergency depa...

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

Mammographic breast density has been established as an independent risk marker for developing breast...

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) pose...

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 radiothera...

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 inv...

[Prediction of three-dimensional dose distribution in intensity-modulated radiation therapy based on neural network learning].

OBJECTIVE: To establish the association between the geometric anatomical characteristics of the pati...

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, sinc...

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 profilin...

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 dr...

Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing ca...

Radiation Oncology Terminology Linker: A Step Towards a Linked Data Knowledge Base.

Performing image feature extraction in radiation oncology is often dependent on the organ and tumor ...

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 enh...

[What Is Necessary for Radiation Technology Studies for Big Data and AI Era?].