AIMC Topic: Carcinoma, Squamous Cell

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Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.

Medical image analysis Nov 24, 2022
Although deep learning (DL) has demonstrated impressive diagnostic performance for a variety of computational pathology tasks, this performance often markedly deteriorates on whole slide images (WSI) generated at external test sites. This phenomenon ...
Carcinoma, Basal Cell Carcinoma, Squamous Cell Deep Learning Humans Skin Neoplasms Australia
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Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology.

Nature communications Nov 2, 2022
A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain of cancer digital histopathology, ...
Deep Learning Adenocarcinoma Humans Uncertainty Carcinoma, Squamous Cell
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Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

International journal of molecular sciences Sep 8, 2022
In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a dee...
Biomarkers Carcinoma, Squamous Cell Biomarkers, Tumor Humans Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms NF-kappa B Mouth Neoplasms Metformin Gefitinib Deep Learning Systems Biology Drug Design Gene Expression Regulation, Neoplastic Drug Discovery
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A deep learning-based model predicts survival for patients with laryngeal squamous cell carcinoma: a large population-based study.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery Aug 28, 2022
OBJECTIVES: To assess the performance of DeepSurv, a deep learning-based model in the survival prediction of laryngeal squamous cell carcinoma (LSCC) using the Surveillance, Epidemiology, and End Results (SEER) database.
Deep Learning Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Prognosis Carcinoma, Squamous Cell Neoplasm Staging Laryngeal Neoplasms Humans
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Deep-learning-based classification of desmoplastic reaction on H&E predicts poor prognosis in oesophageal squamous cell carcinoma.

Histopathology Jul 11, 2022
AIMS: Desmoplastic reaction (DR) categorisation has been shown to be a promising prognostic factor in oesophageal squamous cell carcinoma (ESCC). The usual DR evaluation is performed using semiquantitative scores, which can be subjective. This study ...
Prognosis Carcinoma, Squamous Cell Deep Learning Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Humans
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Intelligent Deep Learning Enabled Oral Squamous Cell Carcinoma Detection and Classification Using Biomedical Images.

Computational intelligence and neuroscience Jun 30, 2022
Oral cancer is one of the lethal diseases among the available malignant tumors globally, and it has become a challenging health issue in developing and low-to-middle income countries. The prognosis of oral cancer remains poor because over 50% of pati...
Mouth Neoplasms Deep Learning Humans Carcinoma, Squamous Cell Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms
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Transoral robotic cordectomy for glottic carcinoma: a rapid review.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery Jun 22, 2022
OBJECTIVE: The objective of this study was to investigate feasibility, surgical, oncological, and functional outcomes of transoral robotic cordectomy (TORS-Co) and whether TORS-Co reported comparable outcomes of transoral laser microsurgery (TLM).
Laryngeal Neoplasms Robotics Humans Robotic Surgical Procedures Carcinoma, Squamous Cell Tongue Neoplasms Treatment Outcome
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A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study.

Oral oncology Jun 8, 2022
OBJECTIVE: Tissue slides from Oral cavity squamous cell carcinoma (OC-SCC), particularly the epithelial regions, hold morphologic features that are both diagnostic and prognostic. Yet, previously developed approaches for automated epithelium segmenta...
Head and Neck Neoplasms Mouth Neoplasms Image Processing, Computer-Assisted Squamous Cell Carcinoma of Head and Neck Humans Machine Learning Retrospective Studies Carcinoma, Squamous Cell Deep Learning
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Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Journal of dental research Apr 21, 2022
Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor prognosis. OSCC is typically diagnosed from tissue biopsy sections by pathologists who rely on their empirical experience. Deep learning models may improve ...
Humans Head and Neck Neoplasms Carcinoma, Squamous Cell Mouth Neoplasms Deep Learning Squamous Cell Carcinoma of Head and Neck
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Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks.

Scientific reports Feb 24, 2022
In radiation oncology, predicting patient risk stratification allows specialization of therapy intensification as well as selecting between systemic and regional treatments, all of which helps to improve patient outcome and quality of life. Deep lear...
Aged, 80 and over Adult Biomarkers, Tumor Neoplasm Recurrence, Local Head and Neck Neoplasms Attention Carcinoma, Squamous Cell Positron Emission Tomography Computed Tomography Aged Diagnosis, Computer-Assisted Prognosis Male Humans Deep Learning Retrospective Studies Middle Aged Neural Networks, Computer Image Processing, Computer-Assisted Quality of Life Female
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