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Head and Neck Neoplasms

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Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessment in Head and Neck Cancer.

JAMA network open
IMPORTANCE: Sarcopenia is an established prognostic factor in patients with head and neck squamous cell carcinoma (HNSCC); the quantification of sarcopenia assessed by imaging is typically achieved through the skeletal muscle index (SMI), which can b...

A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and valid...

Effectiveness of deep learning classifiers in histopathological diagnosis of oral squamous cell carcinoma by pathologists.

Scientific reports
The study aims to identify histological classifiers from histopathological images of oral squamous cell carcinoma using convolutional neural network (CNN) deep learning models and shows how the results can improve diagnosis. Histopathological samples...

Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives.

Seminars in cancer biology
Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate anatomical structure of these regions poses considerable challenges to effi...

Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics.

Cancer research communications
UNLABELLED: Artificial intelligence (AI) and machine learning (ML) are becoming critical in developing and deploying personalized medicine and targeted clinical trials. Recent advances in ML have enabled the integration of wider ranges of data includ...

Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data.

Computers in biology and medicine
BACKGROUND: Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis.

Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews.

Advances in therapy
INTRODUCTION: Several studies have emphasized the potential of artificial intelligence (AI) and its subfields, such as machine learning (ML), as emerging and feasible approaches to optimize patient care in oncology. As a result, clinicians and decisi...

Head and neck tumor segmentation convolutional neural network robust to missing PET/CT modalities using channel dropout.

Physics in medicine and biology
. Radiation therapy for head and neck (H&N) cancer relies on accurate segmentation of the primary tumor. A robust, accurate, and automated gross tumor volume segmentation method is warranted for H&N cancer therapeutic management. The purpose of this ...

Effect of radiotherapy on phagocytosis percentage and index in patients with oral squamous cell carcinoma.

Journal of cancer research and therapeutics
BACKGROUND: Phagocytosis plays an important role in the fundamental process of immunity and maintains systemic tissue homeostasis. Phagocytosis function is assessed in radiotherapy to signify the prognosis of patient. Therefore, we designed a study t...

Realistic CT data augmentation for accurate deep-learning based segmentation of head and neck tumors in kV images acquired during radiation therapy.

Medical physics
BACKGROUND: Using radiation therapy (RT) to treat head and neck (H&N) cancers requires precise targeting of the tumor to avoid damaging the surrounding healthy organs. Immobilisation masks and planning target volume margins are used to attempt to mit...