AI Medical Compendium Topic:
Biomarkers, Tumor

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A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Oncotype DX(ODX) is a 21-gene breast cancer recurrence score(RS) assay that aids in decision-making for chemotherapy in early-stage hormone receptor-positive(HR+)breast cancer. We developed a prediction tool using machine learning for hig...

G2Vec: Distributed gene representations for identification of cancer prognostic genes.

Scientific reports
Identification of cancer prognostic genes is important in that it can lead to accurate outcome prediction and better therapeutic trials for cancer patients. Many computational approaches have been proposed to achieve this goal; however, there is room...

Application of Artificial Neural Network in miRNA Biomarker Selection and Precise Diagnosis of Colorectal Cancer.

Iranian biomedical journal
BACKGROUND: The early diagnosis of colorectal cancer (CRC) is associated with improved survival rates, and development of novel non-invasive, sensitive, and specific diagnostic tests is highly demanded. The objective of this paper was to identify com...

Distribution based Fuzzy Estimate Spectral Clustering for Cancer Detection with Protein Sequence and Structural Motifs.

Asian Pacific journal of cancer prevention : APJCP
Objective: In biological data analysis, protein sequence and structural motifs are an amino-acid sequence patterns that are widespread and used as tools for detecting the cancer at an earlier stage. To improve the cancer detection with minimum space ...

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...

Segmentation of glandular epithelium in colorectal tumours to automatically compartmentalise IHC biomarker quantification: A deep learning approach.

Medical image analysis
In this paper, we propose a method for automatically annotating slide images from colorectal tissue samples. Our objective is to segment glandular epithelium in histological images from tissue slides submitted to different staining techniques, includ...

High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to use machine learning to predict abdominal recurrence on CT on the basis of serial cancer antigen 125 (CA125) levels in patients with advanced high-grade serous ovarian cancer on surveillance.

Urinary Polyamine Biomarker Panels with Machine-Learning Differentiated Colorectal Cancers, Benign Disease, and Healthy Controls.

International journal of molecular sciences
Colorectal cancer (CRC) is one of the most daunting diseases due to its increasing worldwide prevalence, which requires imperative development of minimally or non-invasive screening tests. Urinary polyamines have been reported as potential markers to...

A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.

Nature communications
Cancers that appear pathologically similar often respond differently to the same drug regimens. Methods to better match patients to drugs are in high demand. We demonstrate a promising approach to identify robust molecular markers for targeted treatm...