Latest AI and machine learning research in obstetrics & gynecology for healthcare professionals.
Accurate segmentation of ultrasound (US) images of the cervical muscles is crucial for precision healthcare. The demand for automatic computer-assisted methods is high. However, the scarcity of labeled data hinders the development of these methods. Advanced semi-supervised learning approaches have displayed promise in overcoming this challenge by utilizing labeled and unlabeled data. This study ...
In the contemporary fight against cancer, primary health care (PHC) services hold a significant and critical position within the healthcare system. This study, as one of the most detailed investigations into cancer research in primary care, comprehensively evaluates cancer studies from the perspective of PHC using bibliometric techniques and machine learning. The dataset for the analyses was sourc...
Accurate prediction of food delivery times significantly impacts customer satisfaction, operational efficiency, and profitability in food delivery s...
Invisible labor is an intrinsic part of the modern workplace, and includes labor that is undervalued or unrecognized such as creating collaborative ...
T2 hyperintensities in spinal cord MR images are crucial biomarkers for conditions such as degenerative cervical myelopathy. However, current clinic...
Real-time computer-aided diagnosis using artificial intelligence (AI), with images, can help oncologists diagnose cancer with high accuracy and in a...
Background: Accurate spinal structure measurement is crucial for assessing spine health and diagnosing conditions like spondylosis, disc herniation,...
Early detection of cervical cancer is crucial for improving patient outcomes and reducing mortality by identifying precancerous lesions as soon as p...
To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination. Cervical cyt...
The deployment of computer-aided diagnosis systems for cervical cancer screening using whole slide images (WSIs) faces critical challenges due to do...
Cervical spondylosis, a complex and prevalent condition, demands precise and efficient diagnostic techniques for accurate assessment. While MRI offe...
Mobile robots are essential in applications such as autonomous delivery and hospitality services. Applying learning-based methods to address mobile ...
STUDY QUESTION: How can we best achieve tissue segmentation and cell counting of multichannel-stained endometriosis sections to understand tissue comp...
In recent years, the transfer of more than one embryo has become less frequent to diminish multiple pregnancies. Even so, there is still a risk of one...
The objective of the present study was to examine the relationship between the gases in a cow's uterine environment and its ovarian physiological stru...
OBJECTIVE: To develop machine learning models, facilitate a more accurate diagnosis of ovarian cancer (OC), and explore potential markers.
This study presents a comparative evaluation of a Variational Autoencoder (VAE) enhanced with Minimum Description Length (MDL) regularization agains...
Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesio...
Pap smear image quality is crucial for cervical cancer detection. This study introduces an optimized hybrid approach that combines the Perona-Malik ...
The increasing demand for efficient last-mile delivery in smart logistics underscores the role of autonomous robots in enhancing operational efficie...