AIMC Topic: Carcinoma, Squamous Cell

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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Membrane Transport Proteins Monte Carlo Method Serpins Adenocarcinoma of Lung Cystatin A Datasets as Topic Tumor Suppressor Proteins Adenosine Triphosphatases Terminology as Topic Computational Biology Machine Learning Humans Gene Expression Regulation, Neoplastic Carcinoma, Squamous Cell Transcription Factors Gene Expression Profiling Diagnosis, Differential Transcriptome Cadherins Lung Neoplasms
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Machine learning identifies 10 feature miRNAs for lung squamous cell carcinoma.

Gene Apr 13, 2020
Lung squamous cell carcinoma (LUSC) is a common type of malignancy. The mechanism behind its tumor progression is not clear yet. The aim of this study is to use machine learning to identify the feature miRNAs, which can be reliably used as biomarkers...
Male Middle Aged Lung Neoplasms RNA, Messenger MicroRNAs Humans Machine Learning Female Carcinoma, Squamous Cell Biomarkers, Tumor
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Real world study for the concordance between IBM Watson for Oncology and clinical practice in advanced non-small cell lung cancer patients at a lung cancer center in China.

Thoracic cancer Mar 19, 2020
BACKGROUND: IBM Watson for Oncology (WFO) provides physicians with evidence-based treatment options. This study was designed to explore the concordance of the suggested therapeutic regimen for advanced non-small cell lung (NSCLC) cancer patients betw...
Patient Selection Practice Guidelines as Topic Evidence-Based Medicine Adenocarcinoma of Lung Lung Neoplasms United States Carcinoma, Non-Small-Cell Lung Follow-Up Studies Prognosis Retrospective Studies Clinical Decision-Making Female Carcinoma, Squamous Cell Survival Rate Male Middle Aged China Decision Support Systems, Clinical Humans Artificial Intelligence
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Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

Journal of the European Academy of Dermatology and Venereology : JEADV Mar 4, 2020
BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) wit...
Humans Skin Neoplasms Carcinoma, Squamous Cell Aged Aged, 80 and over Male Neural Networks, Computer Forecasting Phenotype Retrospective Studies Female Neoplasm Staging Neoplasm Recurrence, Local Radiotherapy Dosage Scalp Middle Aged Treatment Outcome Head and Neck Neoplasms Age Factors
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Machine learning helps identifying volume-confounding effects in radiomics.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 20, 2020
Highlighting the risk of biases in radiomics-based models will help improve their quality and increase usage as decision support systems in the clinic. In this study we use machine learning-based methods to identify the presence of volume-confounding...
Radiometry Laryngeal Neoplasms Oropharyngeal Neoplasms Female Carcinoma, Non-Small-Cell Lung Carcinoma, Squamous Cell Cluster Analysis Aged Regression Analysis Software Aged, 80 and over Male Principal Component Analysis Algorithms Humans Adult Middle Aged Databases, Factual Machine Learning Decision Support Systems, Clinical Retrospective Studies Lung Neoplasms Tomography, X-Ray Computed Squamous Cell Carcinoma of Head and Neck
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Automated oral squamous cell carcinoma identification using shape, texture and color features of whole image strips.

Tissue & cell Dec 4, 2019
Despite profound knowledge of the incidence of oral cancers and a large body of research beyond it, it continues to beat diagnosis and treatment management. Post physical observation by clinicians, a biopsy is a gold standard for accurate detection o...
Cell Nucleus Male Humans Image Processing, Computer-Assisted Artificial Intelligence Biopsy Female Mouth Neoplasms Carcinoma, Squamous Cell Datasets as Topic
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Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

European radiology Nov 11, 2019
OBJECTIVE: To develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting apparent diffusion coefficient (ADC) radiomics feature...
Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Uterine Cervical Neoplasms Middle Aged Deep Learning Image Processing, Computer-Assisted Carcinoma Humans Retrospective Studies Female Carcinoma, Squamous Cell Tumor Burden Diffusion Magnetic Resonance Imaging
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Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.

Clinical lung cancer Oct 21, 2019
INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall survival (OS) for patients with locally advanced non-small-cell lung cancer (NSCLC). However, radiation-induced cardiac toxicity among patients with ea...
Cardiotoxicity Humans Neural Networks, Computer Follow-Up Studies Neoplasm Staging Radiotherapy Dosage Radiosurgery Survival Rate Retrospective Studies Male Female Middle Aged Carcinoma, Squamous Cell Lung Neoplasms Aged Carcinoma, Non-Small-Cell Lung Aged, 80 and over
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Machine learning methods applied to audit of surgical outcomes after treatment for cancer of the head and neck.

The British journal of oral & maxillofacial surgery Jul 26, 2019
Most surgical specialties have attempted to address concerns about unfair comparison of outcomes by "risk-adjusting" data to benchmark specialty-specific outcomes that are indicative of the quality of care. We are building on previous work in head an...
Treatment Outcome Head and Neck Neoplasms Clinical Audit Humans Machine Learning Carcinoma, Squamous Cell Postoperative Complications
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CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification.

Oral radiology Jun 13, 2019
OBJECTIVE: To clarify CT diagnostic performance in extranodal extension of cervical lymph node metastases using deep learning classification.
Humans Tomography, X-Ray Computed Carcinoma, Squamous Cell Deep Learning Lymph Nodes Lymphatic Metastasis Mouth Neoplasms Extranodal Extension
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