AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cervix Uteri

Showing 1 to 10 of 60 articles

Clear Filters

BMT: A Cross-Validated ThinPrep Pap Cervical Cytology Dataset for Machine Learning Model Training and Validation.

Scientific data
In the past several years, a few cervical Pap smear datasets have been published for use in clinical training. However, most publicly available datasets consist of pre-segmented single cell images, contain on-image annotations that must be manually e...

An automatic cervical cell classification model based on improved DenseNet121.

Scientific reports
The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical...

Generalizable deep neural networks for image quality classification of cervical images.

Scientific reports
Successful translation of artificial intelligence (AI) models into clinical practice, across clinical domains, is frequently hindered by the lack of image quality control. Diagnostic models are often trained on images with no denotation of image qual...

Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis.

BMC pregnancy and childbirth
Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is significant, as understanding the precise biochemical processes can provide critical insights into the mechanisms of labor and potentially inform better ...

Discussion of a Simple Method to Generate Descriptive Images Using Predictive ResNet Model Weights and Feature Maps for Recurrent Cervix Cancer.

Tomography (Ann Arbor, Mich.)
BACKGROUND: Predictive models like Residual Neural Networks (ResNets) can use Magnetic Resonance Imaging (MRI) data to identify cervix tumors likely to recur after radiotherapy (RT) with high accuracy. However, there persists a lack of insight into m...

[Diagnostic performance evaluation of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination. Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of t...

A deep ensemble learning approach for squamous cell classification in cervical cancer.

Scientific reports
Cervical cancer, arising from the cells of the cervix, the lower segment of the uterus connected to the vagina-poses a significant health threat. The microscopic examination of cervical cells using Pap smear techniques plays a crucial role in identif...

Detection of precancerous lesions in cervical images of perimenopausal women using U-net deep learning.

African journal of reproductive health
Due to physiological changes during the perimenopausal period, the morphology of cervical cells undergoes certain alterations. Accurate cell image segmentation and lesion identification are of great significance for the early detection of precancerou...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Nature communications
Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytology slides from 17,397 women and test it on 10,826 additional cases through a three-stage process. Th...