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Uterine Cervical Neoplasms

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Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms.

Photodiagnosis and photodynamic therapy
Cervical cancer is the most common reproductive malignancy in the female reproductive system. The incidence rate and mortality rate of cervical cancer among women in China are high. In this study, Raman spectroscopy was used to collect tissue sample ...

Development and validation of a deep learning survival model for cervical adenocarcinoma patients.

BMC bioinformatics
BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for cervical adenocarcinoma patients and process personalized survival prediction.

Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.

Physics in medicine and biology
. The purpose of this study was to evaluate the accuracy of brachytherapy (BT) planning structures derived from Deep learning (DL) based auto-segmentation compared with standard manual delineation for postoperative cervical cancer.. We introduced a c...

Ant Colony Optimization-Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer.

BioMed research international
Cancer is characterized by abnormal cell growth and proliferation, which are both diagnostic indicators of the disease. When cancerous cells enter one organ, there is a risk that they may spread to adjacent tissues and eventually to other organs. Can...

Robot-assisted versus conventional laparoscopic radical hysterectomy in cervical cancer stage IB1.

International journal of medical sciences
The aim of this study was to compare survival outcomes of robot-assisted laparoscopic radical hysterectomy (RRH) and conventional laparoscopic radical hysterectomy (LRH) in cervical cancer stage IB1. This is a retrospective study of patients with c...

Using deep learning to predict survival outcome in non-surgical cervical cancer patients based on pathological images.

Journal of cancer research and clinical oncology
PURPOSE: We analyzed clinical features and the representative HE-stained pathologic images to predict 5-year overall survival via the deep-learning approach in cervical cancer patients in order to assist oncologists in designing the optimal treatment...

Application of EfficientNet-B0 and GRU-based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions.

Cancer medicine
BACKGROUND: Colposcopy is indispensable for the diagnosis of cervical lesions. However, its diagnosis accuracy for high-grade squamous intraepithelial lesion (HSIL) is at about 50%, and the accuracy is largely dependent on the skill and experience of...

Cervical cell classification with deep-learning algorithms.

Medical & biological engineering & computing
Cervical cancer is a serious threat to the lives and health of women. The accurate analysis of cervical cell smear images is an important diagnostic basis for cancer identification. However, pathological data are often complex and difficult to analyz...

A generalization performance study on the boosting radiotherapy dose calculation engine based on super-resolution.

Zeitschrift fur medizinische Physik
PURPOSE: During the radiation treatment planning process, one of the time-consuming procedures is the final high-resolution dose calculation, which obstacles the wide application of the emerging online adaptive radiotherapy techniques (OLART). There ...

RESOLVE-DWI-based deep learning nomogram for prediction of normal-sized lymph node metastasis in cervical cancer: a preliminary study.

BMC medical imaging
BACKGROUND: It is difficult to predict normal-sized lymph node metastasis (LNM) in cervical cancer clinically. We aimed to investigate the feasibility of using deep learning (DL) nomogram based on readout segmentation of long variable echo-trains dif...