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Biomarkers, Tumor

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A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk.

Breast cancer research : BCR Jul 29, 2019
BACKGROUND: Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mas...
Neoplasm Staging Neoplasm Grading Mastectomy Carcinoma, Intraductal, Noninfiltrating Neoplasm Recurrence, Local Breast Neoplasms Biomarkers, Tumor Middle Aged Risk Assessment Immunohistochemistry Proportional Hazards Models Humans Machine Learning Prognosis Female Aged Aged, 80 and over Adult
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Wx: a neural network-based feature selection algorithm for transcriptomic data.

Scientific reports Jul 19, 2019
Next-generation sequencing (NGS), which allows the simultaneous sequencing of billions of DNA fragments simultaneously, has revolutionized how we study genomics and molecular biology by generating genome-wide molecular maps of molecules of interest. ...
Datasets as Topic RNA, Neoplasm Humans Genes, Neoplasm Neural Networks, Computer Algorithms Biomarkers, Tumor Neoplasms Gene Expression Profiling Transcriptome High-Throughput Nucleotide Sequencing
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In-Bore Transrectal MRI-Guided Biopsy With Robotic Assistance in the Diagnosis of Prostate Cancer: An Analysis of 57 Patients.

AJR. American journal of roentgenology Jul 3, 2019
The objective of our study was to analyze the feasibility and potential role of robotic-assisted transrectal MRI-guided biopsy for the diagnosis of prostate cancer. A total of 57 patients (mean age, 67 ± 6 [SD] years; age range, 57-83 years; mean p...
Retrospective Studies Aged Aged, 80 and over Biomarkers, Tumor Male Humans Neoplasm Grading Rectum Feasibility Studies Image-Guided Biopsy Magnetic Resonance Imaging, Interventional Middle Aged Robotics Prostatic Neoplasms Prostate-Specific Antigen
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Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer.

JAMA network open Jul 3, 2019
IMPORTANCE: Immunohistochemistry (IHC) is the most widely used assay for identification of molecular biomarkers. However, IHC is time consuming and costly, depends on tissue-handling protocols, and relies on pathologists' subjective interpretation. I...
Algorithms Retrospective Studies Female Reproducibility of Results Breast Neoplasms Humans Artificial Intelligence Tissue Array Analysis Biomarkers, Tumor Feasibility Studies Middle Aged Immunohistochemistry ROC Curve Receptor, ErbB-2 Predictive Value of Tests Receptors, Estrogen British Columbia
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C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.

Computer methods and programs in biomedicine Jun 29, 2019
BACKGROUND AND OBJECTIVE: Over the last two decades, DNA microarray technology has emerged as a powerful tool for early cancer detection and prevention. It helps to provide a detailed overview of disease complex microenvironment. Moreover, online ava...
Neoplasms Computational Biology Support Vector Machine Early Detection of Cancer Gene Expression Heuristics Oligonucleotide Array Sequence Analysis Predatory Behavior Social Behavior Tumor Microenvironment Biomarkers, Tumor Animals Male Humans Computer Simulation Machine Learning Female Software Reproducibility of Results Algorithms Sensitivity and Specificity Databases, Factual
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Recognition of early and late stages of bladder cancer using metabolites and machine learning.

Metabolomics : Official journal of the Metabolomic Society Jun 20, 2019
INTRODUCTION: Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and ...
Neoplasm Staging Insulin Amino Acids ROC Curve Proto-Oncogene Proteins c-akt Galactose Urinary Bladder Neoplasms Glycine ErbB Receptors Metabolic Networks and Pathways Humans Area Under Curve Machine Learning Software Biomarkers, Tumor
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Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Molecules (Basel, Switzerland) Jun 4, 2019
Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two l...
Models, Biological Molecular Targeted Therapy Antineoplastic Agents ROC Curve Bayes Theorem Workflow Algorithms Reproducibility of Results Biomarkers, Tumor Drug Discovery Humans Neural Networks, Computer Machine Learning
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Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.

Cancer gene therapy May 29, 2019
Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature white blood cells from the bone marrow. Therapy resistance resulting from the persistence of leukemia stem cells (LSCs) are found in numerous patient...
Feasibility Studies Computational Biology Humans Models, Genetic Datasets as Topic Biomarkers, Tumor Drug Resistance, Neoplasm Leukemia, Myeloid, Acute Support Vector Machine Monte Carlo Method Gene Expression Profiling Neoplastic Stem Cells
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Assessment of risk based on variant pathways and establishment of an artificial neural network model of thyroid cancer.

BMC medical genetics May 28, 2019
BACKGROUND: This study aimed to establish an artificial neural network (ANN) model based on variant pathways to predict the risk of thyroid cancer.
Cluster Analysis Humans Thyroid Neoplasms Neural Networks, Computer Gene Regulatory Networks Risk Factors Gene Expression Regulation, Neoplastic Biomarkers, Tumor Signal Transduction Gene Expression Profiling
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Method for Identifying Cancer-Related Genes Using Gene Similarity-Based Collaborative Filtering.

Journal of computational biology : a journal of computational molecular cell biology May 22, 2019
Humans Machine Learning Female Breast Neoplasms Biomarkers, Tumor RNA-Seq Models, Genetic Genes, Neoplasm
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