Latest AI and machine learning research in pregnancy for healthcare professionals.
Combination strategy is crucial for enhancing cancer therapeutic efficacy, but co-delivery of multiple active pharmaceutical ingredients (APIs) remains challenging. Although nanomedicines address spatiotemporal co-delivery of APIs, it typically requires extensive excipients and formulation screening, which hampers drug discovery efficiency. Herein, we have developed a data-driven design workflow a...
Super-resolution ultrasound imaging (SRUI) surpasses the diffraction limit of conventional ultrasound, enabling visualization of microvascular architecture and hemodynamics with potential applications in neurology, oncology, and cardiology. However, clinical adoption remains limited by complex parameter optimization, subjective interpretation, and time-consuming workflows. We present a multimodal ...
PURPOSE: Large-scale biomedical analysis in prostate cancer requires structured, tabular datasets, yet most clinical documentation remains in free-tex...
BACKGROUND: Preeclampsia with severe features is a major contributor to maternal and perinatal morbidity and mortality, particularly in low- and middl...
Rare diseases impose a disproportionate clinical burden, and yet therapeutic progress is hindered by small cohorts, biological heterogeneity, and limi...
Gene delivery for neurodegenerative cerebral disorders faces formidable structural and practical challenges. The blood-brain, blood- cerebrospinal flu...
OBJECTIVES: Ultrasonography is increasingly the preferred method for infant hip screening to enable timely diagnosis and treatment of developmental dy...
BACKGROUND: Axillary lymph node metastasis (ALNM) is a critical prognostic factor in breast cancer. While sentinel lymph node biopsy remains the gold ...
PURPOSE: This study aimed to develop an artificial intelligence-based scoring system to prioritize mosaic embryos according to live birth outcomes. ME...
Coronary heart disease (CHD) and carotid artery disease (CAD) often co-occur. However, conventional diagnosis typically involves separate, site-by-sit...
Background Clinicians frequently face questions that require rapid, evidence-based answers. Artificial intelligence (AI) tools are increasingly used f...
PURPOSE: The purpose of this study was to develop a machine learning-based algorithm based on a combination of magnetic resonance imaging (MRI) and co...
Supramolecular PdnL2n architectures are versatile molecular platforms with applications spanning catalysis, sensing, and therapeutic delivery. Whereas...
Myocardial infarction (MI) is a life-threatening condition caused by reduced oxygen supply to the heart muscle due to blockage of the coronary arterie...
BACKGROUND: Videolaryngoscopy (VL) is recommended as a first-line technique for tracheal intubation; however, existing airway assessment tools-largely...
BACKGROUND: Prediction of Large for Gestational Age (LGA) risk is important as it can enable earlier, more effective interventions, and avoid or mitig...
Traumatic brain injury (TBI) is a leading cause of persistent cognitive, motor, and neuropsychiatric impairment, arising from both the initial mechani...
AI is transforming drug delivery system (DDS) design by enabling predictive modeling and inverse design strategies. Recent advances integrating machin...
OBJECTIVES: To investigate the performance of an artificial intelligence (AI) diagnostic system for thyroid nodule sonography based on deep learning c...
Embryo transfer (ET) is a fundamental biotechnology in modern dairy production, utilized to maximize the propagation of superior genetics and circumve...