Obstetrics & Gynecology

The taming of sociodigital anticipations: AI in the digital welfare state.

Advanced algorithmic technologies and artificial intelligence (AI) are projected to profoundly impact public employment services (PES) and the delivery of labor market policies. Focusing on the perspectives of PES counselors in Austria, this study examines workers' anticipations of future AI technologies. Based on face-to-face interviews ( = 23), it identifies and explores the concept of "taming" ...

Nanocarrier-based targeted drug delivery for Alzheimer's disease: addressing neuroinflammation and enhancing clinical translation.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, amyloid-beta (Aβ) aggregation, tau pathology, and chronic neuroinflammation. Among these, neuroinflammation plays a crucial role in exacerbating disease progression, making it an attractive therapeutic target. However, the presence of the blood-brain barrier (BBB) significantly limits the effec...

Artificial intelligence based advancements in nanomedicine for brain disorder management: an updated narrative review.

Nanomedicines are nanoscale, biocompatible materials that offer promising alternatives to conventional treatment options for brain disorders. The rece...

Identification and validation of immune-related and inflammation-related genes in endometriosis.

AIM: Endometriosis is characterized by immune evasion and progressive inflammation. This study aimed to identify key genes related to immune and infla...

Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census.

BACKGROUND: Although immune checkpoint inhibitors (ICIs) represent a substantial breakthrough in cancer treatment, it is crucial to acknowledge that t...

Comprehensive analysis of potential biomarkers for the diagnosis and prognosis of Cervical squamous cell carcinoma - based on GEO and TCGA databases.

BACKGROUND: Cervical squamous cell carcinoma (CESC) constitutes a substantial global health burden, especially in resource-limited regions. The identi...

Pyroptosis-Related Gene Signatures Enable Robustly Diagnosis, Prognosis and Immune Responses Prediction in Uterine Corpus Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignancy with poor prognosis and high lethality rates. Pyroptosis, a pro-inflammator...

Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms.

BACKGROUND: Programmed cell death (PCD) refers to a regulated and active process of cellular demise, initiated by specific biological signals. PCD pla...

Deep learning approaches for quantitative and qualitative assessment of cervical vertebral maturation staging systems.

To investigate the potential of artificial intelligence (AI) in Cervical Vertebral Maturation (CVM) staging, we developed and compared AI-based qualit...

Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy.

BACKGROUND: Gynecological cancers are among the most prevalent cancers in women worldwide. Brachytherapy, often used as a boost to external beam radio...

Advancing Pharmaceutical Science with Artificial Neural Networks: A Review on Optimizing Drug Delivery Systems Formulation.

Drug Delivery Systems (DDS) have been developed to address the challenges associated with traditional drug delivery methods. These DDS aim to improve ...

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans.

Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2...

Exploration of Cervical Cancer Image Processing and Detection Based on URCNNs.

BACKGROUND: Cervical cancer is a prevalent malignancy among women, often asymptomatic in early stages, complicating detection.

Using machine learning to predict patients with polycystic ovary disease in Chinese women.

OBJECTIVE: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorder...

Analyzing Demographic Grocery Purchase Patterns in Kenyan Supermarkets Through Unsupervised Learning Techniques.

Kenya is experiencing a significant increase in the prevalence of non-communicable diseases (NCDs) such as cardiovascular diseases, hypertension, Type...

Leveraging AI for Automatic Classification of PCOS Using Ultrasound Imaging

The AUTO-PCOS Classification Challenge seeks to advance the diagnostic capabilities of artificial intelligence (AI) in identifying Polycystic Ovary ...

A Review on the Integration of Artificial Intelligence and Medical Imaging in IVF Ovarian Stimulation

Artificial intelligence (AI) has emerged as a powerful tool to enhance decision-making and optimize treatment protocols in in vitro fertilization (I...

From General to Specific: Tailoring Large Language Models for Personalized Healthcare

The rapid development of large language models (LLMs) has transformed many industries, including healthcare. However, previous medical LLMs have lar...

Efficacy of Temporal Interference Electrical Stimulation for Spinal Cord Injury Rehabilitation: A Case Series

Spinal cord injury (SCI) is a debilitating condition that often results in significant motor and sensory deficits, impacting the quality of life. Cu...

Uncovering Student Engagement Patterns in Moodle with Interpretable Machine Learning

Understanding and enhancing student engagement through digital platforms is critical in higher education. This study introduces a methodology for qu...