AI Medical Compendium Topic:
Neoplasm Staging

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Deep Learning for Clinical Image Analyses in Oral Squamous Cell Carcinoma: A Review.

JAMA otolaryngology-- head & neck surgery
IMPORTANCE: Oral squamous cell carcinoma (SCC) is a lethal malignant neoplasm with a high rate of tumor metastasis and recurrence. Accurate diagnosis, prognosis prediction, and metastasis detection can improve patient outcomes. Deep learning for clin...

Magnetic resonance imaging-based artificial intelligence model in rectal cancer.

World journal of gastroenterology
Rectal magnetic resonance imaging (MRI) is the preferred method for the diagnosis of rectal cancer as recommended by the guidelines. Rectal MRI can accurately evaluate the tumor location, tumor stage, invasion depth, extramural vascular invasion, and...

Robotic surgical staging of lymphadenectomy during pregnancy - case report.

Ceska gynekologie
OBJECTIVE: We aim to present a case of a 43-year-old patient dia-gnosed with cervical adenocarcinoma in the 15th week of pregnancy, who underwent robotically-assisted staging in a laparoscopic pelvic lymphadenectomy. Further therapeutic approach was ...

Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

Technology in cancer research & treatment
To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the Cycle...

[Prostate cancer pathologic features in men ≤55 years treated with robot assisted radical prostatectomy.].

Archivos espanoles de urologia
OBJECTIVE: Among western males, prostate cancer is the most frequent oncological disease. Since the widespread of PSA, diagnoses in younger adults is increasing. The aim of this study is to analyze pathological features and biochemical recurrence eve...

Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer.

JCO clinical cancer informatics
PURPOSE: For patients with early-stage breast cancer, predicting the risk of metastatic relapse is of crucial importance. Existing predictive models rely on agnostic survival analysis statistical tools (eg, Cox regression). Here we define and evaluat...

Evaluation of Prognosis in Nasopharyngeal Cancer Using Machine Learning.

Technology in cancer research & treatment
BACKGROUND AND AIM: Although the prognosis of nasopharyngeal cancer largely depends on a classification based on the tumor-lymph node metastasis staging system, patients at the same stage may have different clinical outcomes. This study aimed to eval...