Pregnancy

Darwinian Nanomedicine: Artificial Intelligence-Driven Evolutionary Drug Delivery for Adaptive and Precision Therapeutics.

OBJECTIVE: This review presents Darwinian nanomedicine as an artificial intelligence (AI)-enabled drug delivery strategy that applies Darwinian evolutionary principles as a computational and engineering analogy. Rather than implying biological evolution of nanoparticles, the framework employs iterative cycles of variation, selection, adaptation, and computational inheritance to optimize nanopartic...

Automated fetal magnetic resonance imaging lung segmentation for rapid lung volume estimation across diverse pulmonary hypoplasia phenotypes.

BACKGROUND: Fetal magnetic resonance imaging (MRI)-derived lung volume measurements are used for prenatal risk stratification in conditions associated with pulmonary hypoplasia, but manual segmentation is time-intensive. OBJECTIVE: To evaluate whether automated fetal MRI lung segmentation enables rapid and reliable volumetric assessment across diverse pulmonary hypoplasia phenotypes. MATERIALS AND...

The daily dynamics of algorithmic pressure and traffic safety in gig delivery: a multilevel mediation model of risky riding.

The rapid expansion of on-demand food delivery has brought algorithmic management, the use of artificial intelligence to oversee labor processes, into...

Engineering extracellular vesicles for targeted siRNA delivery: Advances, therapeutic applications, and clinical translation.

Small interfering RNA (siRNA) therapeutics have emerged as a transformative approach for sequence-specific gene silencing, offering the potential to t...

Ultrasound Habitat Radiomics for Preoperative Prediction of Invasive Breast Cancer With a DCIS Component: A Dual-center Retrospective Study.

PURPOSE: To develop and externally validate an ultrasound-based habitat subregional radiomics model for preoperative prediction of invasive breast can...

Emerging Trends in the Integration of Nanotechnology and 3D Printing for Next-Generation Drug Delivery Systems.

OBJECTIVE: To provide a comprehensive overview of three-dimensional (3D) printing as an emerging manufacturing approach in pharmaceutical and biomedic...

Comparative evaluation of large language models for text-based diagnostic reasoning in fetal central nervous system MRI: A retrospective single-center diagnostic accuracy study.

Fetal magnetic resonance imaging (MRI) plays an important role in evaluating prenatal central nervous system (CNS) abnormalities, but expert interpret...

Systematic review of mental or behavioral health care in integrated specialty medical care settings.

INTRODUCTION: Although the integration of mental health services is widely accepted as important in primary care, the benefits for specialty medical c...

Explainable ensemble machine learning for pregnancy screening in dairy cows using routine dairy herd improvement records.

Early identification of non-pregnant dairy cows is important for minimizing days open, yet current pregnancy diagnosis methods require additional cost...

3D epigenome of glial cell types in developing human cortex.

The human cortex is complex and heterogeneous, undergoing extensive expansion during development1,2. Our prior study of neurogenesis, including radial...

Artificial intelligence and big data from digital health applications: publication trends and analysis.

PURPOSE: The integration of big data with artificial intelligence in the field of digital health has brought a new dimension to healthcare service del...

Real-time MRI-ultrasound image translation under limited paired data using a physically motivated conditional GAN.

Objective. Magnetic resonance imaging (MRI) and ultrasound (US) provide complementary anatomical and intraoperative information, yet their large appea...

Assessing digital health curriculum needs: a mixed-methods study of student and faculty perspectives in a Singapore medical school.

BACKGROUND: The rapid advancement of digital technologies has transformed healthcare delivery, creating an imperative for medical education to integra...

Multiscale Switch for Semi-Supervised and Contrastive Learning in Medical Ultrasound Image Segmentation.

Medical ultrasound (US) image segmentation faces significant challenges due to limited labeled data and characteristic imaging artifacts, including sp...

Insights into the use of artificial intelligence in the drug discovery and delivery of nanosystems for the treatment of infectious diseases and neoplasms.

Artificial Intelligence (AI) has become a fundamental driver of scientific progress, particularly in disease diagnosis, drug development, and drug del...

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and...

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomi...

Calibrating artificial intelligence against human expertise using femoral nerve segmentation on ultrasound: a consensus framework.

INTRODUCTION: Meaningful validation of artificial intelligence for medical image interpretation requires comparison against human expert performance, ...

Multitask learning for ultrasound image classification and segmentation of endometrium in the diagnosis of ectopic pregnancy.

OBJECTIVE: To develop an automated tool that performs classification and segmentation of endometrium for ectopic pregnancy diagnosis before gestationa...

Evaluating the Accuracy, Empathy, and Readability of Generative AI Versus Registered Nurses in Discharge Planning: A Vignette-Based Study.

AIM: To compare the multidimensional performance of discharge instructions generated by generative AI (GPT-4) versus those created by clinical registe...