Obstetrics & Gynecology

Machine learning of Raman spectra predicts drug release from polysaccharide coatings for targeted colonic delivery.

Colonic drug delivery offers numerous pharmaceutical opportunities, including direct access to local...

Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms.

: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical ...

Endometriosis Online Communities: How Machine Learning Can Help Physicians Understand What Patients Are Discussing Online.

STUDY OBJECTIVE: Use machine learning to characterize the content of endometriosis online community ...

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

To assess the value of deep learning in selecting the optimal embryo for in vitro fertilization, a m...

Factors affecting biochemical pregnancy loss (BPL) in preimplantation genetic testing for aneuploidy (PGT-A) cycles: machine learning-assisted identification.

PURPOSE: To determine the factors influencing the likelihood of biochemical pregnancy loss (BPL) aft...

Pilot study of machine learning for detection of placenta accreta spectrum.

DeepBP: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN.

INTRODUCTION: The blood-brain barrier (BBB) serves as a critical structural barrier and impedes the ...

Predicting Metformin Efficacy in Improving Insulin Sensitivity Among Women With Polycystic Ovary Syndrome and Insulin Resistance: A Machine Learning Study.

OBJECTIVE: Metformin is clinically effective in treating polycystic ovary syndrome (PCOS) with insul...

Single-detector multiplex imaging flow cytometry for cancer cell classification with deep learning.

Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged ...

Personalized approach to malignant struma ovarii: Insights from a web-based machine learning tool.

OBJECTIVES: Malignant struma ovarii (MSO) is a rare ovarian tumor characterized by mature thyroid ti...

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

Artificial intelligence can standardize and automatize highly demanding procedures, such as manual s...

Integrating Deep Learning-Based Dose Distribution Prediction with Bayesian Networks for Decision Support in Radiotherapy for Upper Gastrointestinal Cancer.

PURPOSE: Selecting the better techniques to harbor optimal motion management, either a stereotactic ...

Biorobotic Drug Delivery for Biomedical Applications.

Despite extensive efforts, current drug-delivery systems face biological barriers and difficulties i...

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30...

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

OBJECTIVES: The roles of magnetic resonance imaging (MRI) -based radiomics approach and deep learnin...

Identification of programmed cell death-related genes and diagnostic biomarkers in endometriosis using a machine learning and Mendelian randomization approach.

BACKGROUND: Endometriosis (EM) is a prevalent gynecological disorder frequently associated with irre...

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

Deep learning, especially Convolution Neural Networks (CNNs), has demonstrated superior performance ...

Magnetic-actuated hydrogel microrobots with multimodal motion and collective behavior.

Magnetic-actuated miniature robots have sparked growing interest owing to their promising potential ...

Image Quality Assessment of a Deep Learning-Based Automatic Bone Removal Algorithm for Cervical CTA.

BACKGROUND: The present study aims to evaluate the postprocessing image quality of a deep-learning (...

A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.

Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed...

Artificial intelligence in predicting postoperative heterotopic ossification following anterior cervical disc replacement.

OBJECTIVE: This study aimed to develop and validate a machine learning (ML) model to predict high-gr...