AIMC Topic: Neoplasm Grading

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Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Clinical cancer research : an official journal of the American Association for Cancer Research
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...

Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.

Computers in biology and medicine
OBJECTIVE: The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach.

Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

Journal of neuro-oncology
INTRODUCTION: Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a gl...

Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

Artificial intelligence in medicine
OBJECTIVE: Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on the texture features obtained from the lumen, nuclei, cytoplasm and stroma, all of which are import...

Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study.

Scientific reports
We sought to investigate, whether texture analysis of diffusional kurtosis imaging (DKI) enhanced by support vector machine (SVM) analysis may provide biomarkers for gliomas staging and detection of the IDH mutation. First-order statistics and textur...

A Multi-scale U-Net for Semantic Segmentation of Histological Images from Radical Prostatectomies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Gleason grading of histological images is important in risk assessment and treatment planning for prostate cancer patients. Much research has been done in classifying small homogeneous cancer regions within histological images. However, semi-supervis...

A Deep Belief Network and Dempster-Shafer-Based Multiclassifier for the Pathology Stage of Prostate Cancer.

Journal of healthcare engineering
OBJECT: Pathologic prediction of prostate cancer can be made by predicting the patient's prostate metastasis prior to surgery based on biopsy information. Because biopsy variables associated with pathology have uncertainty regarding individual patien...

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

Computer methods and programs in biomedicine
BACKGROUND: Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) co...

HCV nonstructural protein 4 is associated with aggressiveness features of breast cancer.

Breast cancer (Tokyo, Japan)
BACKGROUND: Hepatitis C virus (HCV) has the lymphotropic feature that is supposed to be the reason of related extrahepatic manifestation. HCV viral oncoproteins may participate in the regulation of some gene expression that has been implicated in tum...