: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. : A...
OBJECTIVE: To generate a nomogram based on preoperative parameters to predict the occurrence of a major complication within 30-days of robotic partial nephrectomy.
Clinical cancer research : an official journal of the American Association for Cancer Research
Apr 16, 2019
PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypot...
Clinical cancer research : an official journal of the American Association for Cancer Research
Apr 11, 2019
PURPOSE: We aimed to evaluate the value of deep learning on positron emission tomography with computed tomography (PET/CT)-based radiomics for individual induction chemotherapy (IC) in advanced nasopharyngeal carcinoma (NPC).
OBJECTIVES: To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.
Advancements are constantly being made in oncology, improving prevention and treatment of cancers. To help reduce the impact and deadliness of cancers, they must be detected early. Additionally, there is a risk of cancers recurring after potentially ...
Traditional radiomics models mainly rely on explicitly-designed handcrafted features from medical images. This paper aimed to investigate if deep features extracted via transfer learning can generate radiomics signatures for prediction of overall sur...
International journal of radiation oncology, biology, physics
Oct 19, 2016
PURPOSE: To assess the efficacy of robotic-assisted laparoscopic sentinel lymph node (SLN) dissection (SLND) to select those patients with prostate cancer (PCa) who would benefit from additional pelvic external beam radiation therapy and long-term an...
PROBLEM SETTING: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine ...