AIMC Topic: Uterine Cervical Neoplasms

Clear Filters Showing 91 to 100 of 334 articles

CINNAMON-GUI: Revolutionizing Pap Smear Analysis with CNN-Based Digital Pathology Image Classification.

F1000Research
BACKGROUND: Medical imaging has seen significant advancements through machine learning, particularly convolutional neural networks (CNNs). These technologies have transformed the analysis of pathological images, enhancing the accuracy of diagnosing a...

Automated segmentation in pelvic radiotherapy: A comprehensive evaluation of ATLAS-, machine learning-, and deep learning-based models.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Artificial intelligence can standardize and automatize highly demanding procedures, such as manual segmentation, especially in an anatomical site as common as the pelvis. This study investigated four automated segmentation tools on computed tomograph...

Integrating MRI-based radiomics and clinicopathological features for preoperative prognostication of early-stage cervical adenocarcinoma patients: in comparison to deep learning approach.

Cancer imaging : the official publication of the International Cancer Imaging Society
OBJECTIVES: The roles of magnetic resonance imaging (MRI) -based radiomics approach and deep learning approach in cervical adenocarcinoma (AC) have not been explored. Herein, we aim to develop prognosis-predictive models based on MRI-radiomics and cl...

Random forests for the analysis of matched case-control studies.

BMC bioinformatics
BACKGROUND: Conditional logistic regression trees have been proposed as a flexible alternative to the standard method of conditional logistic regression for the analysis of matched case-control studies. While they allow to avoid the strict assumption...

A two-stream decision fusion network for cervical pap-smear image classification tasks.

Tissue & cell
Deep learning, especially Convolution Neural Networks (CNNs), has demonstrated superior performance in image recognition and classification tasks. They make complex pattern recognition possible by extracting image features through layers of abstracti...

Utilising deep learning networks to classify ZEB2 expression images in cervical cancer.

British journal of hospital medicine (London, England : 2005)
Cervical cancer continues to be a significant cause of cancer-related deaths among women, especially in low-resource settings where screening and follow-up care are lacking. The transcription factor zinc finger E-box-binding homeobox 2 (ZEB2) has be...

The role of radiomics for predicting of lymph-vascular space invasion in cervical cancer patients based on artificial intelligence: a systematic review and meta-analysis.

Journal of gynecologic oncology
The primary aim of this study was to conduct a methodical examination and assessment of the prognostic efficacy exhibited by magnetic resonance imaging (MRI)-derived radiomic models concerning the preoperative prediction of lymph-vascular space infil...

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review.

International journal of cancer
The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound imaging in gynecology oncology. Web of Science, PubMed, and Scopus databases were searched. All studies were imported to RAYYAN QCRI software. The ove...