Obstetrics & Gynecology

Bone visualization of the cervical spine with deep learning-based synthetic CT compared to conventional CT: A single-center noninferiority study on image quality.

PURPOSE: To investigate whether the image quality of a specific deep learning-based synthetic CT (sC...

Pragmatic Prediction of Excessive Length of Stay After Cervical Spine Surgery With Machine Learning and Validation on a National Scale.

BACKGROUND: Extended postoperative hospital stays are associated with numerous clinical risks and in...

Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.

Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian can...

The Impact of the Live Delivery of Goods on Consumers' Purchasing Behaviour in Complex Situations Based on Artificial Intelligence Technology.

With the development of information technology, the purchase of goods online has acquired a differen...

Spinning-enabled wireless amphibious origami millirobot.

Wireless millimeter-scale origami robots have recently been explored with great potential for biomed...

Is the Cardiovascular Specialist Ready For the Fifth Revolution? The Role of Artificial Intelligence, Machine Learning, Big Data Analysis, Intelligent Swarming, and Knowledge-Centered Service on the Future of Global Cardiovascular Healthcare Delivery.

Diagnosis and Nursing Intervention of Gynecological Ovarian Endometriosis with Magnetic Resonance Imaging under Artificial Intelligence Algorithm.

This research was aimed to study the application value of the magnetic resonance imaging (MRI) diagn...

Oxygen delivery in pediatric cardiac surgery and its association with acute kidney injury using machine learning.

OBJECTIVE: Acute kidney injury (AKI) after pediatric cardiac surgery with cardiopulmonary bypass (CP...

Deep learning features encode interpretable morphologies within histological images.

Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learn...

Radiomics and artificial intelligence in malignant uterine body cancers: Protocol for a systematic review.

INTRODUCTION: Uterine body cancers (UBC) are represented by endometrial carcinoma (EC) and uterine s...

Real-time denoising of ultrasound images based on deep learning.

Ultrasound images are widespread in medical diagnosis for muscle-skeletal, cardiac, and obstetrical ...

Deep Learning Algorithm-Based Magnetic Resonance Imaging Feature-Guided Serum Bile Acid Profile and Perinatal Outcomes in Intrahepatic Cholestasis of Pregnancy.

This study was aimed to explore magnetic resonance imaging (MRI) based on deep learning belief netwo...

Deep Learning Algorithm-Based Ultrasound Image Information in Diagnosis and Treatment of Pernicious Placenta Previa.

This study was to explore the value of the deep dictionary learning algorithm in constructing a B ul...

AL-Net: Attention Learning Network Based on Multi-Task Learning for Cervical Nucleus Segmentation.

Cervical nucleus segmentation is a crucial and challenging issue in automatic pathological diagnosis...

Prediction of Labor Unemployment Based on Time Series Model and Neural Network Model.

With the advent of big data, statistical accounting based on artificial intelligence can realistical...

Objective and Subjective Assessment of Bladder Function after Robot-assisted Laparoscopic Radical Hysterectomy for Early-stage Cervical Cancer.

STUDY OBJECTIVE: To examine whether objective bladder function after robot-assisted radical hysterec...

Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh.

Intended pregnancy is one of the significant indicators of women's well-being. Globally, 74 million ...

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolu...

Deep learning-based multimodal image analysis for cervical cancer detection.

Cervical cancer is the fourth most common cancer in women, and its precise detection plays a critica...

Formulation design and optimization of cationic-charged liposomes of brimonidine tartrate for effective ocular drug delivery by design of experiment (DoE) approach.

OBJECTIVE: The present study was aimed to design and optimize brimonidine tartrate (BRT) loaded cati...

Combining multiparametric MRI features-based transfer learning and clinical parameters: application of machine learning for the differentiation of uterine sarcomas from atypical leiomyomas.

OBJECTIVES: To explore the feasibility and effectiveness of machine learning (ML) based on multipara...