AIMC Topic: Lymphatic Metastasis

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Segmentation of metastatic cervical lymph nodes from CT images of oral cancers using deep-learning technology.

Dento maxillo facial radiology
OBJECTIVE: The purpose of this study was to establish a deep-learning model for segmenting the cervical lymph nodes of oral cancer patients and diagnosing metastatic or non-metastatic lymph nodes from contrast-enhanced computed tomography (CT) images...

Evolved explainable classifications for lymph node metastases.

Neural networks : the official journal of the International Neural Network Society
A novel evolutionary approach for Explainable Artificial Intelligence is presented: the "Evolved Explanations" model (EvEx). This methodology combines Local Interpretable Model Agnostic Explanations (LIME) with Multi-Objective Genetic Algorithms to a...

Multi-energy level fusion for nodal metastasis classification of primary lung tumor on dual energy CT using deep learning.

Computers in biology and medicine
Lymph node metastasis also called nodal metastasis (Nmet), is a clinically primary task for physicians. The survival and recurrence of lung cancer are related to the Nmet staging from Tumor-Node-Metastasis (TNM) reports. Furthermore, preoperative Nme...

Factors Affecting Transperitoneal Robot-Assisted Laparoscopic Radical Prostatectomy.

Journal of laparoendoscopic & advanced surgical techniques. Part A
To evaluate the impact of body mass index (BMI), preoperative risk classification, previous inguinal herniotomy, and abdominal operations on several steps of robot-assisted radical prostatectomy (RARP) and lymph node (LN) involvement. A total numbe...

Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.

The Journal of pathology
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...

Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The preoperative lymph node (LN) status is important for the treatment of colorectal cancer (CRC). Here, we established and validated a deep learning (DPL) model for predicting lymph node metastasis (LNM) in CRC.

Development of a radiomics and machine learning model for predicting occult cervical lymph node metastasis in patients with tongue cancer.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: We aimed to develop a predictive model for occult cervical lymph node metastasis in patients with tongue cancer using radiomics and machine learning from pretreatment contrast-enhanced computed tomography.

Deep learning nomogram for predicting lymph node metastasis using computed tomography image in cervical cancer.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning (DL) has been used on medical images to grade, differentiate, and predict prognosis in many tumors.

Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?

Gynecologic oncology
BACKGROUND: Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic va...