Obstetrics & Gynecology

Diagnosis of uterine diseases by label-free serum SERS fingerprints with machine learning.

Early detection of uterine diseases is critically important for women's reproductive health. Here, we propose a novel and robust serum-based SERS analysis platform that integrates machine learning algorithms. This is the first application of it in the diagnosis and classification of various uterine diseases. We firstly collected serum samples from a cohort consisting of 27 healthy volunteers and 6...

Machine learning approaches for the prediction of retained placenta in dairy cows.

Retained placenta (RP) is a reproductive disorder that causes significant financial losses to the dairy industry. Predicting RP risk in cows post-calving is a challenging task. This study aimed to evaluate the predictive capabilities of five machine learning algorithms Naïve Bayes (NB), Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and XGBoost along with Logistic Regression...

Evaluating the added value of salivary hormones in the context of menstrual cycle staging: A machine learning approach and app-implementation.

OBJECTIVE: Salivary hormone assessment is commonly used in menstrual cycle studies, but its validity for accurate menstrual cycle staging has been que...

Portable Biomechanics Laboratory: Clinically Accessible Movement Analysis from a Handheld Smartphone

The way a person moves is a direct reflection of their neurological and musculoskeletal health, yet it remains one of the most underutilized vital s...

Attend-and-Refine: Interactive keypoint estimation and quantitative cervical vertebrae analysis for bone age assessment

In pediatric orthodontics, accurate estimation of growth potential is essential for developing effective treatment strategies. Our research aims to ...

Learning from Sparse Point Labels for Dense Carcinosis Localization in Advanced Ovarian Cancer Assessment

Learning from sparse labels is a challenge commonplace in the medical domain. This is due to numerous factors, such as annotation cost, and is espec...

Magneto-radiative modelling and artificial neural network optimization of biofluid flow in a stenosed arterial domain

The increasing complexity of cardiovascular diseases and limitations in traditional healing methods mandate the invention of new drug delivery syste...

Vers un cadre ontologique pour la gestion des comp{é}tences : {à} des fins de formation, de recrutement, de m{é}tier, ou de recherches associ{é}es

The rapid transformation of the labor market, driven by technological advancements and the digital economy, requires continuous competence developme...

Serum-Based Detection of Pancreatic and Ovarian Cancer via a Nanoparticle-Enhanced Fluorescence Array and Machine Learning.

: Early detection of oncological diseases such as pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer (OV) is pivotal for successful treatment ...

Artificial intelligence models using F-wave responses predict amyotrophic lateral sclerosis.

Nerve conduction F-wave studies contain crucial information about subclinical motor dysfunction that can be used to diagnose patients with amyotrophic...

ViTaL: A Multimodality Dataset and Benchmark for Multi-pathological Ovarian Tumor Recognition

Ovarian tumor, as a common gynecological disease, can rapidly deteriorate into serious health crises when undetected early, thus posing significant ...

Beyond Olfaction: New Insights into Human Odorant Binding Proteins

Until today, the exact function of mammalian odorant binding proteins (OBPs) remains a topic of debate. Although their main established function lac...

LANTERN: A Machine Learning Framework for Lipid Nanoparticle Transfection Efficiency Prediction

The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a critical bottleneck for RNA-based thera...

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training

Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like ...

HRProfiler Detects Homologous Recombination Deficiency in Breast and Ovarian Cancers Using Whole-Genome and Whole-Exome Sequencing Data.

UNLABELLED: Breast and ovarian cancers harboring homologous recombination deficiency (HRD) are sensitive to PARP inhibitors and platinum chemotherapy....

Leveraging Whole-Exome Sequencing and Mutational Signatures to Detect Homologous Recombination Deficiency in Cancer.

Homologous recombination is a high-fidelity DNA repair mechanism essential for maintaining genome stability. Impairment of this pathway, often due to ...

Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.

Since the discovery of the life-saving hormone insulin in 1921 by Dr. Frederick Banting in 1921, there have been many critical discoveries and technic...

Radiomics analysis of intraoral ultrasonographic images for prediction of late cervical lymph node metastasis in patients with tongue cancer: influence of marginal region.

OBJECTIVES: To investigate the predictability of late cervical lymph node metastasis using radiomics analysis of ultrasonographic images of tongue can...

Deep Learning Model for Real-Time Nuchal Translucency Assessment at Prenatal US.

Purpose To develop and evaluate an artificial intelligence-based model for real-time nuchal translucency (NT) plane identification and measurement in ...

Assessment of the efficacy and accuracy of cervical cytology screening with the Hologic Genius Digital Diagnostics System.

BACKGROUND: Medical technologies powered by artificial intelligence are quickly transforming into practical solutions by rapidly leveraging massive am...