AIMC Topic: Biomarkers, Tumor

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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...
Databases, Factual Computer Simulation Female Reproducibility of Results Sensitivity and Specificity Humans Machine Learning Software Algorithms Oligonucleotide Array Sequence Analysis Predatory Behavior Social Behavior Computational Biology Support Vector Machine Early Detection of Cancer Gene Expression Heuristics Tumor Microenvironment Biomarkers, Tumor Animals Male Neoplasms
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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 ...
Glycine Galactose ErbB Receptors Metabolic Networks and Pathways Area Under Curve Neoplasm Staging Amino Acids Proto-Oncogene Proteins c-akt Humans Machine Learning Software Biomarkers, Tumor Insulin ROC Curve Urinary Bladder Neoplasms
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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...
Antineoplastic Agents Machine Learning Algorithms Workflow ROC Curve Humans Models, Biological Bayes Theorem Reproducibility of Results Neural Networks, Computer Molecular Targeted Therapy Biomarkers, Tumor Drug Discovery
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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...
Datasets as Topic Drug Resistance, Neoplasm Monte Carlo Method Humans Biomarkers, Tumor Leukemia, Myeloid, Acute Gene Expression Profiling Computational Biology Models, Genetic Support Vector Machine Neoplastic Stem Cells Feasibility Studies
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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.
Signal Transduction Cluster Analysis Humans Risk Factors Neural Networks, Computer Biomarkers, Tumor Gene Expression Profiling Thyroid Neoplasms Gene Regulatory Networks Gene Expression Regulation, Neoplastic
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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
Breast Neoplasms Biomarkers, Tumor RNA-Seq Models, Genetic Genes, Neoplasm Humans Machine Learning Female
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Breast cancer outcome prediction with tumour tissue images and machine learning.

Breast cancer research and treatment May 22, 2019
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.
Microscopy Survival Analysis Tumor Burden Neoplasm Metastasis Immunohistochemistry Image Processing, Computer-Assisted Follow-Up Studies Neoplasm Staging Neoplasm Grading Workflow Kaplan-Meier Estimate Humans Machine Learning Prognosis Female Aged Aged, 80 and over Adult Breast Neoplasms Biomarkers, Tumor Middle Aged
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Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

Journal of cellular and molecular medicine Apr 18, 2019
BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival outcome and associations with differentially expressed Genes (RNA Sequencing) in groups of glioblastoma multiforme (GBM) patients.
Magnetic Resonance Imaging Biomarkers, Tumor Brain Neoplasms Glioblastoma Aged Male Humans Aged, 80 and over Transcriptome Radiographic Image Interpretation, Computer-Assisted Middle Aged Machine Learning Young Adult Adolescent Gene Expression Profiling Algorithms Adult ROC Curve Prognosis Survival Rate Genomics Female Gene Expression Regulation, Neoplastic
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Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 16, 2019
PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypot...
Cytokines Male Prospective Studies Carcinoma, Non-Small-Cell Lung Humans Middle Aged Female ROC Curve Models, Statistical Machine Learning Aged Lung Neoplasms Radiotherapy Biomarkers, Tumor Nomograms Radiation Pneumonitis
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Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 11, 2019
PURPOSE: We aimed to develop an ovarian cancer-specific predictive framework for clinical stage, histotype, residual tumor burden, and prognosis using machine learning methods based on multiple biomarkers.
Survival Rate Biomarkers, Tumor Middle Aged ROC Curve Support Vector Machine Ovarian Neoplasms Bayes Theorem Neoplasm Staging Neoplasm Grading Carcinoma, Ovarian Epithelial Female Humans Aged Preoperative Care Aged, 80 and over Neural Networks, Computer Young Adult Artificial Intelligence Adult Machine Learning Algorithms Prognosis
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