Latest AI and machine learning research in pregnancy for healthcare professionals.
As artificial intelligence (AI) becomes increasingly embedded in healthcare delivery, this chapter explores the critical aspects of developing reliable and ethical Clinical Decision Support Systems (CDSS). Beginning with the fundamental transition from traditional statistical models to sophisticated machine learning approaches, this work examines rigorous validation strategies and performance as...
Foundational models have emerged as powerful tools for addressing various tasks in clinical settings. However, their potential development to breast ultrasound analysis remains untapped. In this paper, we present BUSGen, the first foundational generative model specifically designed for breast ultrasound image analysis. Pretrained on over 3.5 million breast ultrasound images, BUSGen has acquired ...
Developing reliable healthcare AI models requires training with representative and diverse data. In imbalanced datasets, model performance tends to ...
Traditional ultrasound simulators solve the wave equation to model pressure distribution fields, achieving high accuracy but requiring significant c...
Temporal embryo images and parental fertility table indicators are both valuable for pregnancy prediction in \textbf{in vitro fertilization embryo t...
The Mice Autism Detection via Ultrasound Vocalization (MADUV) Challenge introduces the first INTERSPEECH challenge focused on detecting autism spect...
Ultrasound images are commonly formed by sequential acquisition of beam-steered scan-lines. Minimizing the number of required scan-lines can signifi...
With the dramatic upsurge in the volume of ultrasound examinations, low-quality ultrasound imaging has gradually increased due to variations in oper...
Lung ultrasound is a growing modality in clinics for diagnosing and monitoring acute and chronic lung diseases due to its low cost and accessibility...
Accurate and robust ultrasound image segmentation is critical for computer-aided diagnostic systems. Nevertheless, the inherent challenges of ultras...
Overcoming biological barriers remains the paramount challenge for pulmonary mRNA therapeutics. Conventional approaches focus exclusively on passively...
The ability to differentiate between viable and dead microorganisms in metagenomic data is crucial for various microbial inferences, ranging from asse...
Nanomedicine requires smart delivery systems that are precise, robust, and universal. While liposomes are established vehicles in drug delivery, their...
Effective treatment of chronic pain remains hindered by the lack of drug delivery systems that simultaneously achieve long-term stability, high spatia...
Medical microrobots promise to increase the efficacy and reduce the invasiveness of certain medical procedures in the future. Real-time tracking of th...
Endosomal escape remains a major barrier to effective nucleic acid delivery via lipid nanoparticles (LNPs). Here, we address this challenge by incorpo...
Metabolic transformations in female mammals throughout gestation manifest in the metabolite profiles of bodily fluids, potentially serving as biomarke...
Repeated pregnancy loss (RPL) is a multifactorial condition in which the underlying immunological mechanisms remain incompletely understood. Although ...
Neural circuits emerge during development through dynamic interactions between genetic instructions and environmental cues that shape cell fate, conne...
In vivo genetic engineering of T cells could overcome the logistical, biological, and safety challenges of ex vivo modification, but effective and saf...