AIMC Journal:
BMC cancer

Showing 151 to 160 of 162 articles

A convolutional neural network-based system to classify patients using FDG PET/CT examinations.

BMC cancer Mar 17, 2020
BACKGROUND: As the number of PET/CT scanners increases and FDG PET/CT becomes a common imaging modality for oncology, the demands for automated detection systems on artificial intelligence (AI) to prevent human oversight and misdiagnosis are rapidly ...
Humans Neural Networks, Computer Artificial Intelligence Female Aged Thoracic Neoplasms Head and Neck Neoplasms Positron Emission Tomography Computed Tomography Fluorodeoxyglucose F18 Pelvic Neoplasms Abdominal Neoplasms Aged, 80 and over Young Adult Adult Male Middle Aged
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A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies.

BMC cancer Sep 5, 2019
BACKGROUND: Predicting lung adenocarcinoma (LUAD) risk is crucial in determining further treatment strategies. Molecular biomarkers may improve risk stratification for LUAD.
Proportional Hazards Models Multivariate Analysis Kaplan-Meier Estimate Survival Rate Genes, Neoplasm Humans Adenocarcinoma of Lung Biomarkers, Tumor Transcriptome Machine Learning Male Prognosis Follow-Up Studies Middle Aged Lung Neoplasms Female Databases, Genetic Gene Expression Regulation, Neoplastic Disease Progression Aged Disease-Free Survival
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Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA.

BMC cancer Aug 23, 2019
BACKGROUND: Blood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion...
Humans Machine Learning Biomarkers, Tumor Male Middle Aged Gene Expression Profiling Transcriptome ROC Curve Female Reproducibility of Results Aged Aged, 80 and over Colorectal Neoplasms Genomics Computational Biology Neoplasm Staging Genome, Human Circulating Tumor DNA
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Artificial neural network models to predict nodal status in clinically node-negative breast cancer.

BMC cancer Jun 21, 2019
BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical s...
Receptors, Estrogen Sentinel Lymph Node Biopsy Carcinoma, Lobular Axilla Area Under Curve Tumor Burden Neovascularization, Pathologic Linear Models Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Breast Neoplasms Middle Aged Lymph Nodes Lymphatic Metastasis Humans Neural Networks, Computer
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Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.

BMC cancer May 17, 2019
PURPOSE: To explore imaging biomarkers that can be used for diagnosis and prediction of pathologic stage in non-small cell lung cancer (NSCLC) using multiple machine learning algorithms based on CT image feature analysis.
Carcinoma, Non-Small-Cell Lung Neoplasm Staging Image Interpretation, Computer-Assisted Machine Learning Tomography, X-Ray Computed Humans Female Male Lung Neoplasms
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LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features.

BMC cancer Mar 22, 2019
BACKGROUND: Lung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction...
Lung Neoplasms Genomics Computational Biology Support Vector Machine Datasets as Topic Feasibility Studies Mutation Adenocarcinoma of Lung Models, Biological Humans Survival Analysis Precision Medicine Prognosis Survival Rate Biomarkers, Tumor ROC Curve
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Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

BMC cancer May 30, 2018
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...
Adult Breast Neoplasms Middle Aged ROC Curve Image Processing, Computer-Assisted Neoplasm Staging Genetic Testing Breast Staining and Labeling Predictive Value of Tests Principal Component Analysis Prognosis Female Risk Factors Models, Biological Aged Humans Supervised Machine Learning Young Adult Cell Nucleus Receptors, Estrogen
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Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

BMC cancer Dec 12, 2017
BACKGROUND: Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for ...
Support Vector Machine Follow-Up Studies Survival Analysis Hysterectomy Aged Humans Adult Middle Aged Neural Networks, Computer Uterine Cervical Neoplasms Female Postoperative Complications ROC Curve
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Robot-assisted radical prostatectomy significantly reduced biochemical recurrence compared to retro pubic radical prostatectomy.

BMC cancer Jun 29, 2017
BACKGROUND: The pathological and oncological outcomes of retro-pubic radical prostatectomy (RRP) and robot-assisted radical prostatectomy (RARP) have not been sufficiently investigated.
Follow-Up Studies Humans Aged, 80 and over Robotics Survival Rate Prostatic Neoplasms Laparoscopy Male Neoplasm Recurrence, Local Middle Aged Treatment Outcome Prostatectomy Retrospective Studies Pubic Bone Aged
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Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

BMC cancer Dec 1, 2016
BACKGROUND: Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machi...
Middle Aged Female Models, Theoretical Chemotherapy, Adjuvant Humans Aged Patient Care Team Antineoplastic Combined Chemotherapy Protocols Machine Learning Aged, 80 and over Combined Modality Therapy Algorithms Adult Supervised Machine Learning Computer Simulation Breast Neoplasms Clinical Decision-Making
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