Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothes...
OBJECTIVES: To develop and validate an algorithm to predict occult nodal metastasis in clinically node negative oral cavity squamous cell carcinoma (OCSCC) using machine learning. To compare algorithm performance to a model based on tumor depth of in...
The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from s...
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 31, 2018
BACKGROUND AND PURPOSE: Intensity-modulated radiation therapy (IMRT) is currently indicated to treat anal squamous cell carcinoma (ASCC). Conformal dose delivery and steep dose gradients may cause marginal misses. We analyzed patterns of locoregional...
American journal of obstetrics and gynecology
Dec 21, 2018
BACKGROUND: Historically, the Cox proportional hazard regression model has been the mainstay for survival analyses in oncologic research. The Cox proportional hazard regression model generally is used based on an assumption of linear association. How...
BACKGROUND: A fully convolutional neural networks (FCN)-based automated image analysis algorithm to discriminate between head and neck cancer and noncancerous epithelium based on nonlinear microscopic images was developed.
BACKGROUND AND AIMS: The prognosis of esophageal cancer is relatively poor. Patients are usually diagnosed at an advanced stage when it is often too late for effective treatment. Recently, artificial intelligence (AI) using deep learning has made rem...
Identification of various constituent layers such as epithelial, subepithelial, and keratin of oral mucosa and characterization of keratin pearls within keratin region as well, are the important and mandatory tasks for clinicians during the diagnosis...
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