Obstetrics & Gynecology

Latest AI and machine learning research in obstetrics & gynecology for healthcare professionals.

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ADAPTIVE MULTI-SCALE GRAPH TRANSFORMER FRAMEWORK FOR HISTOPATHOLOGICAL IMAGES

Whole slide images (WSIs) contain hierarchical information from cellular to tissue architecture but ...

Traces of parenthood but not pregnancy loss in UK Biobank structural brain MRI data

Pregnancy induces neuroanatomical changes in the human brain. Earlier studies detected traces of mot...

A transcription factor-responsive enhancer discovery platform for targeted immunotherapy

Synthetic enhancers with high specificity are crucial for therapeutic gene control. Although existin...

Inter- and intra-individual differences in brain sex map to neuroendocrine profiles

Sex hormone fluctuations modulate structural and functional brain dynamics, yet little is known how ...

Beyond one-size-fits-all: single-cell transcriptomic signatures predict drug efficacy and reveal responder subgroups in endometriosis

Endometriosis affects ∼10% of reproductive-age women, yet targeted non-hormonal therapies remain una...

Biologically Inspired Digital Histology for Deep Phenotyping of Placental Composition Changes Across Major Lesion Types

Placenta pathology provides diagnostic insights for understanding pregnancy complications and guides...

Epigenetic profile drives accurate survival prediction in breast cancer via a multi-omics machine learning model

Accurate overall survival (OS) prediction is key for personalized treatment in breast cancer, but mu...

Integrative multiomic analysis on single-nucleotide variants identifies candidate genes for human craniofacial malformation

Craniofacial malformation (CFM) is a congenital defect encompassing a wide range of phenotypic prese...

Polli-markers: spectral and chemical biomarkers for detecting cryptic early plant pollination responses

Pollination is essential for plant reproduction, ecosystem resilience and human health. Yet, our cap...

Coxmos: Interpretable survival models for high-dimensional and multi-omic data

Survival analysis in high-dimensional (HD) and multi-block (MB) settings, such as omic and multi-omi...

Modeling and Design of Multi-layered Cylindrical Microcapsules for Intravitreal Controlled Release

Chronic diseases often require repeated oral or local administration, which can compromise patient c...

Retinal vascularization rate predicts retinopathy of prematurity and remains unaffected by low-dose bevacizumab treatment

To assess the rate of retinal vascularisation derived from ultra-widefield (UWF) imaging-based retin...

Automatic segmentation of spinal cord lesions in MS: A robust tool for axial T2-weighted MRI scans

Deep learning models have achieved remarkable success in segmenting brain white matter lesions in mu...

Phenotyping Adolescent Endometriosis: Characterizing Symptom Heterogeneity Through Note- and Patient-Level Clustering

Pelvic pain (dysmenorrhea and non-menstrual) is the most common presentation of adolescent endometri...

Assessing the diagnostic accuracy of artificial intelligence in detecting cervical pre-cancer from pap smear images

The global burden of cervical cancer, with a notable prevalence in regions like Tanzania, highlights...

Ovarian cancer recurrence prediction: comparing confirmatory to real world predictors with machine learning

Ovarian cancer is one of the deadliest cancers in women, with a 5-year survival rate of 17-28% in ad...

Benchmarking pathology foundation models for non-neoplastic pathology in the placenta

Machine learning (ML) applications within diagnostic histopathology have been extremely successful. ...

Deep Learning Study of Alkaptonuria Spinal Disease Assesses Global and Regional Severity and Detects Occult Treatment Status

Deep learning (DL) is increasingly used to analyze medical imaging, but is less refined for rare con...

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