Obstetrics & Gynecology

Deep learning model for automated diagnosis of degenerative cervical spondylosis and altered spinal cord signal on MRI.

BACKGROUND CONTEXT: A deep learning (DL) model for degenerative cervical spondylosis on MRI could enhance reporting consistency and efficiency, addressing a significant global health issue.

Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules.

BACKGROUND: Patients undergo regular clinical follow-up after laminoplasty for cervical myelopathy. However, those whose symptoms significantly improve and remain stable do not need to conform to a regular follow-up schedule. Based on the 1-year postoperative outcomes, we aimed to use a machine-learning (ML) algorithm to predict 2-year postoperative outcomes.

Enhancing pap smear image classification: integrating transfer learning and attention mechanisms for improved detection of cervical abnormalities.

Cervical cancer remains a major global health challenge, accounting for significant morbidity and mortality among women. Early detection through scree...

Artificial intelligence in reproductive endocrinology: an in-depth longitudinal analysis of ChatGPTv4's month-by-month interpretation and adherence to clinical guidelines for diminished ovarian reserve.

OBJECTIVE: To quantitatively assess the performance of ChatGPTv4, an Artificial Intelligence Language Model, in adhering to clinical guidelines for Di...

Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet.

To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined with 3D nnUNet for rapid and consistent autosegmentat...

Comparative study of machine learning and statistical survival models for enhancing cervical cancer prognosis and risk factor assessment using SEER data.

Cervical cancer is a common malignant tumor of the female reproductive system and the leading cause of death among women worldwide. The survival predi...

Machine learning- a new paradigm in nanoparticle-mediated drug delivery to cancerous tissues through the human cardiovascular system enhanced by magnetic field.

Nanoparticle-mediated drug delivery offers a promising approach to targeted cancer therapy, leveraging the ability of nanoparticles to deliver therape...

Shared diagnostic genes and potential mechanisms between polycystic ovary syndrome and recurrent miscarriage revealed by integrated transcriptomics analysis and machine learning.

OBJECTIVE: More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA...

Prediction of primary admission total charges following cervical disc arthroplasty utilizing machine learning.

BACKGROUND CONTEXT: Cervical disc arthroplasty (CDA) has become an increasingly popular alternative to anterior cervical discectomy and fusion, offeri...

[How well does artificial intelligence detect fractures in the cervical spine on CT?].

OBJECTIVE: To compare diagnostic accuracy of artificial intelligence (AI) for cervical spine (C-spine) fracture detection on CT with attending radiolo...

Magnetically Actuated Soft Microrobot with Environmental Adaptative Multimodal Locomotion Towards Targeted Delivery.

The development of environmentally adaptive solutions for magnetically actuated microrobots to enable targeted delivery in complex and confined fluid ...

Machine Learning for the Prediction of Surgical Morbidity in Placenta Accreta Spectrum.

OBJECTIVE:  We sought to create a machine learning (ML) model to identify variables that would aid in the prediction of surgical morbidity in cases of...

Enhancing trainee performance in obstetric ultrasound through an artificial intelligence system: randomized controlled trial.

OBJECTIVE: Performing obstetric ultrasound scans is challenging for inexperienced operators; therefore, the prenatal screening artificial intelligence...

Intratumoral and Peritumoral Radiomics for Predicting the Prognosis of High-grade Serous Ovarian Cancer Patients Receiving Platinum-Based Chemotherapy.

RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL) prognostic model to evaluate the significance of intra- and peritumoral rad...

Concept of flexible no-code automation for complex sample preparation procedures.

Driven by demographic changes and dwindling Science Technology Engineering Mathematics enrolments, our research introduces no-code automation as a str...

Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.

OBJECTIVES: This study aimed to assess the accuracy of machine learning (ML) models with feature selection technique in classifying cervical vertebral...

Artificial Intelligence-Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review.

BACKGROUND: Despite the emerging application of clinical decision support systems (CDSS) in pregnancy care and the proliferation of artificial intelli...

Explainable artificial intelligence models for predicting pregnancy termination among reproductive-aged women in six east African countries: machine learning approach.

Pregnancy termination remains a complex and sensitive issue with approximately 45% of abortions worldwide being unsafe, and 97% of abortions occurring...

Multiparametric MRI-based radiomics combined with 3D deep transfer learning to predict cervical stromal invasion in patients with endometrial carcinoma.

OBJECTIVE: To develop and compare various preoperative cervical stromal invasion (CSI) prediction models, including radiomics, three-dimensional (3D) ...

AI in obstetrics: Evaluating residents' capabilities and interaction strategies with ChatGPT.

In line with the digital transformation trend in medical training, students may resort to artificial intelligence (AI) for learning. This study assess...