Obstetrics & Gynecology

Cervical cancer image analysis: Detection and segmentation using self-guided quantum GANs and musical chairs optimization.

The main cause of cervical cancer emerges from long-term Human Papillomavirus (HPV) infections damaging the cervix. The detection methods produced by deep learning algorithms include many available options yet operating systems typically demonstrate poor performance levels and produce mistakes frequently. The research introduces a cervical cancer identification and segmentation within histopatholo...

Automated acquisition of explainable knowledge from unannotated colposcopic images for predicting the natural course of CIN2.

OBJECTIVE: Cervical intraepithelial neoplasia grade 2 (CIN2) represents a critical turning point in cervical cancer progression. While its natural regression rate reaches 50%-57%, CIN2 can also progress to higher-grade lesions or cervical cancer. Accurately predicting CIN2 outcomes is essential for individualized management and avoiding overtreatment. The present study aimed to develop a deep lear...

Development and validation of a highly accurate multigene gene expression biomarker to predict chemotherapy response in primary triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype lacking estrogen and progesterone receptors and HER2 amplification. Representin...

AI innovations for ovarian and endometrial cancer diagnosis: Methodological challenges and engineering roadmap.

The late-stage presentation of ovarian and endometrial cancers, along with varied imaging characteristics and screening constraints, hinders early dia...

Machine learning-directed massively parallel programmable nucleic acid amplification.

Dynamic regulation of amplification efficiency is pivotal yet challenging in molecular diagnostics and DNA data storage. Here, we develop a thermodyna...

A multiday machine learning framework based on improved-NEQsi for predicting embryo quality and pregnancy outcomes in IVF.

PURPOSE: Current embryo selection is limited by fragmented morphological assessments, high resource demands of image-based Artificial Intelligence, an...

Multitask deep learning models for ultrasound image analysis: identification of high-grade serous ovarian cancer and segmentation of tumor regions and intratumoral solid components.

Digital health technologies in pain management for patients with endometriosis: A scoping review.

OBJECTIVE: This scoping review aimed to map the evidence on how digital health technologies are used for pain management in endometriosis. METHODS: Th...

Development of hematopoietic stem cell-targeted lipid nanoparticles through lipid composition optimization.

Hematopoietic stem cell (HSC)-targeted gene editing holds significant potential for treating hereditary hematopoietic disorders, yet the efficient and...

Integrating liquid biopsies and artificial intelligence for early cancer detection: A systematic review and meta-analysis.

INTRODUCTION: The latest generation of liquid biopsies incorporates multi-omic features, including genomics, methylomics, and fragmentomics. Machine l...

Reimagining Brain Drug Delivery: Mechanistic and Translational Advances in Carbon Nanotube Nanomedicine.

Neurological and neurodegenerative disorders (NDDs) present ongoing therapeutic challenges attributed to the structural complexity of the central nerv...

Nanogels for the targeted delivery of antibiotic and antimicrobial drugs.

Nanoparticle-based drug delivery systems represent a promising platform for advancing biomedical therapies. Among them, nanogels - three‑dimensional, ...

A heterogeneous graph neural network for candidate gene prediction in endometriosis.

OBJECTIVE: Precision medicine applications depend on elucidating the underlying molecular mechanisms of disease. However, many disorders, such as endo...

Microneedle-based theranostics for melanoma: Advances and outlook.

Melanoma represents a highly aggressive malignancy that poses persistent challenges for clinical diagnosis and treatment. Although surgical interventi...

Using artificial intelligence to predict sexual health outcomes in endometriosis: a decision tree model algorithm.

BACKGROUND: Endometriosis profoundly impairs sexual function through complex interactions between pain, hormonal disturbances, psychological distress,...

Diagnostic performance of artificial intelligence for detecting peritoneal and small bowel dissemination in epithelial ovarian cancer using preoperative contrast-enhanced CT imaging.

Identifying Predictive Biomarkers and Immune Infiltration Features in Endometriosis.

Explainable AI for gastrointestinal lesion surveillance and precision targeted drug delivery.

The Internet of Bio-NanoThings (IoBNT) promises revolutionary healthcare applications, particularly in targeted drug delivery. However, major challeng...

Exploring AI Driven Autonomous Vehicles as Mobile Health Units to Expand Access to Healthcare in Underserved Communities.

Access to quality healthcare remains a persistent challenge in many low- and middle-income countries, especially for rural and underserved populations...

Identifying postpartum depression subtypes using natural language processing and clinical notes.

BACKGROUND: Postpartum depression (PPD) remains vastly underdiagnosed, and its clinical heterogeneity is not well understood. Diagnosis codes in elect...