Obstetrics & Gynecology

Digital maternity care in Germany: a cross-sectional web-based survey on midwives' perceptions.

PURPOSE: Maternity care is a central component of any healthcare system and is largely provided by midwives. Considering increasing cost pressures and growing demand for efficiency within the German healthcare system, the development of efficient, digitally supported care models are both encouraged and actively promoted, especially in pregnancy. However, to date, no such model has been sustainably...

Clinically-guided models or foundation models? predicting cervical spondylotic myelopathy from electronic health records.

Cervical spondylotic myelopathy (CSM) is the leading cause of spinal cord dysfunction in older adults, yet diagnosis is frequently delayed due to insidious symptom onset and limited clinical recognition. We developed and externally validated machine learning models using structured electronic health record (EHR) data to predict incident CSM diagnoses up to 30 months in advance. Using data from ~2 ...

3D transformer-based dose prediction in HDR brachytherapy for cervical cancer.

Insights into long-acting reversible contraceptive practices in Sub-Saharan Africa: A machine learning perspective.

INTRODUCTION: Long-acting reversible contraceptives (LARCs) are critical for reducing maternal mortality and unintended pregnancies, yet adoption rema...

CT deep learning radiomics and genomics for predicting staging of epithelial ovarian cancer.

BACKGROUND: Accurate preoperative staging is critical for improving the prognosis, treatment, and survival outcomes of epithelial ovarian cancer (EOC)...

[Computerized intrapartum cardiotocography: current evidence, controversies, and future directions].

Cardiotocography (CTG) is defined as the simultaneous recording of fetal heart rate and uterine contractions. It is used worldwide during labour to as...

Gene Modification: Exploring the potential in treating kidney diseases.

Chronic kidney disease (CKD) is a leading cause of death worldwide. Currently available drugs slow but do not cure or prevent progression to end-stage...

U2AD: Uncertainty-based unsupervised anomaly detection framework for detecting T2 hyperintensity in MRI spinal cord.

T2 hyperintensities in spinal cord MR images are crucial biomarkers for conditions such as degenerative cervical myelopathy (DCM). However, current cl...

Exploring Primary and Interaction Effects of Minor Physical Anomalies: Development and Validation of Prediction Models Using Explainable Machine Learning Algorithms for Early-Onset Schizophrenia.

BACKGROUND AND HYPOTHESIS: Minor physical abnormalities (MPAs) are neurodevelopmental markers that can be traced to prenatal events and may be signifi...

A Mixed Dual-Branch Network for Detecting Cervical Spondylotic Myelopathy and Parkinsonian Syndromes via Gait Analysis.

Cervical spondylotic myelopathy (CSM) and parkinsonian syndromes (PS) present similar motor symptoms, often causing misdiagnosis due to current clinic...

Identification of cell senescence-related genes in spontaneous preterm birth based on bioinformatics analysis and machine learning.

Spontaneous premature birth (SPTB) is a common pregnancy complication; however, few studies have explored cell senescence-related markers in SPTB. Bio...

A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features.

Viruses are a significant threat to human life, as demonstrated by the global COVID-19 pandemic and the Ebola outbreak. Diseases such as smallpox, AID...

Machine learning-enhanced nanofiber systems: A new frontier in controlled drug release.

The use of machine learning (ML) is reshaping the design and optimization of nanofiber-based drug delivery systems (N-DDS). Electrospun nanofibers off...

Tuning pH for the Controlled Formation of Ultrasmall Nanoparticles with Direct Cytosolic Access.

Direct cytosolic delivery of nanoparticles offers advantages by circumventing the endocytic pathway, thereby reducing associated intracellular traffic...

AI-Based D-Amino Acid Substitution for Optimizing Antimicrobial Peptides to Treat Multidrug-Resistant Bacterial Infection.

D-amino acid substitution provides an effective strategy for optimizing antimicrobial peptides (AMPs) by enhancing their stability. However, the absen...

Artificial Intelligence and the Potential Transformation of Mental Health.

IMPORTANCE: The potential of tools using artificial intelligence (AI) to address the many challenges in delivery of mental health care has been widely...

IdentifiHR predicts homologous recombination deficiency in high-grade serous ovarian carcinoma using gene expression.

BACKGROUND: Approximately half of all high-grade serous ovarian carcinomas (HGSCs) have a therapeutically targetable defect in homologous recombinatio...

Assessment of AI-generated responses to common pregnancy questions: A blinded expert evaluation.

INTRODUCTION: We conducted a cross-sectional, blinded expert evaluation of AI-generated answers to 22 frequently asked pregnancy questions to characte...

Artificial intelligence applications in ovarian cancer detection: A systematic literature review of deep learning approaches and clinical translation challenges.

This systematic literature review examines artificial intelligence applications in ovarian cancer detection through analysis of 61 studies published b...

AI-assisted translation in oral and maxillofacial surgery: A comparative evaluation.

OBJECTIVES: English dominates scientific communication, yet non-native speakers face significant barriers in publishing. Artificial intelligence (AI) ...