Artificial

Named entity recognition (NER) is a powerful computer system that utilizes various computing strategies to extract information from raw text input, since the early 1990s. With rapid advancement in AI and computing, NER models have gained significant attention and been serving as foundational tools across numerus professional domains to organize unstructured data for research and practical applications. This is particularly evident in the medical and healthcare fields, where NER models are essential in efficiently extract critical information from complex documents that are challenging for manual review...

The accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical for precisely measuring the angle of progression. The traditional method depends heavily on sonographers manually selecting the imaging plane. This process is not only time-intensive and laborious but also prone to variability based on the clinicians' expertise. Consequently, there is a significant need for an automated method driven by artificial intelligence. To enhance the efficiency and accuracy of identifying the pubic symphysis-fetal head standard plane (PSFHSP), we proposed a streamlined neural network, PSFHSP-Net, based on a modified version of ResNet-18...

The study of rare diseases has long been an area of challenge for medical researchers, with agonizingly slow movement towards improved understanding of pathophysiology and treatments compared with more common illnesses. The push towards evidence-based medicine (EBM), which prioritizes certain types of evidence over others, poses a particular issue when mapped onto rare diseases, which may not be feasibly investigated using the methodologies endorsed by EBM, due to a number of constraints. While other trial designs have been suggested to overcome these limitations (with varying success), perhaps the most recent and enthusiastically adopted is the application of artificial intelligence to rare disease data...

Appropriate needle manipulation to avoid abrupt deformation of fragile vessels is a critical determinant of the success of microvascular anastomosis. However, no study has yet evaluated the area changes in surgical objects using surgical videos. The present study therefore aimed to develop a deep learning-based semantic segmentation algorithm to assess the area change of vessels during microvascular anastomosis for objective surgical skill assessment with regard to the "respect for tissue." The semantic segmentation algorithm was trained based on a ResNet-50 network using microvascular end-to-side anastomosis training videos with artificial blood vessels...

This study aims to investigate the feasibility of using an Artificial Lateral Line system for predicting the real-time position and pose of an undulating swimmer with Carangiform swimming patterns. We established a 3D Computational Fluid Dynamics simulation to replicate the swimming dynamics of a freely swimming mackerel under various motion parameters, calculating the corresponding pressure fields. Using the simulated lateral line data, we trained an artificial neural network to predict the centroid coordinates and orientation of the swimmer...

PURPOSE: The PERSPECTIVE study was a real-world European, non-interventional, multicenter, observational study that evaluated the effectiveness, tolerability, and safety of ciclosporin A (CsA) 0.1% cationic emulsion (CE) in routine clinical practice as a treatment for adults with severe keratitis and dry eye disease (DED) that remained insufficiently controlled with artificial tears. This sub-analysis examined data from ophthalmology clinics in Germany to provide more precise insights into treatment patterns, outcomes, and clinical decision-making related to CsA 0...

IMPORTANCE: To explore the correlation between cortisol levels during first admission day and clinical outcomes. OBJECTIVES: Although most patients exhibit a surge in cortisol levels in response to stress, some suffer from critical illness-related corticosteroid insufficiency (CIRCI). Literature remains inconclusive as to which of these patients are at greater risk of poor outcomes. DESIGN: A retrospective study. SETTING: A surgical ICU (SICU) in a tertiary medical center...

Natural photoactive systems have evolved to harness broad-spectrum light from solar radiation for critical functions such as light perception and photosynthetic energy conversion. Molecular photoswitches, which undergo structural changes upon light absorption, are artificial photoactive tools widely used for developing photoresponsive systems and converting light energy. However, photoswitches generally need to be activated by light of specific narrow wavelength ranges for effective photoconversion, which limits their ability to directly work under sunlight and to efficiently harvest solar energy...

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The objective of this review was to critically examine existing digital applications, tailored for use by citizens and professionals, to provide diet monitoring, diet planning, and precision nutrition. We sought to identify the strengths and weaknesses of such digital applications, while exploring their potential contributions to enhancing public health, and discussed potential developmental pathways. Nutrition is a critical aspect of maintaining good health, with an unhealthy diet being one of the primary risk factors for chronic diseases, such as obesity, diabetes, and cardiovascular disease...

BACKGROUND: Artificial intelligence (AI) such as ChatGPT by OpenAI holds great promise to improve the quality of life of patients with dementia and their caregivers by providing high-quality responses to their questions about typical dementia behaviors. So far, however, evidence on the quality of such ChatGPT responses is limited. A few recent publications have investigated the quality of ChatGPT responses in other health conditions. Our study is the first to assess ChatGPT using real-world questions asked by dementia caregivers themselves...

Cervimycins A-D are bis-glycosylated polyketide antibiotics produced by Streptomyces tendae HKI 0179 with bactericidal activity against Gram-positive bacteria. In this study, cervimycin C (CmC) treatment caused a spaghetti-like phenotype in Bacillus subtilis 168, with elongated curved cells, which stayed joined after cell division, and exhibited a chromosome segregation defect, resulting in ghost cells without DNA. Electron microscopy of CmC-treated Staphylococcus aureus (3 × MIC) revealed swollen cells, misshapen septa, cell wall thickening, and a rough cell wall surface...

BACKGROUND: Ventricular septal rupture (VSR) is a rare but grave complication of acute myocardial infarction (AMI). It is a mechanical complication of myocardial infarction where patients may present either in a compensated state or in cardiogenic shock. The aim of the study is to determine the in-hospital mortality. The study also aims to identify the predictors of outcomes (in-hospital mortality, vasoactive inotrope score (VIS), duration of ICU stay and mechanical ventilation in the postoperative period) and compare the clinical and surgical parameters between survivors and non-survivors...

Artificial switchable catalysis is a new, rapidly expanding field that offers great potential advantages for both homogeneous and heterogeneous catalytic systems. Light irradiation is widely accepted as the best stimulus to artificial switchable chemical systems. In recent years, tremendous progress has been made in the synthesis and application of photo-switchable catalysts that can control when and where bond formation and dissociation take place in reactant molecules. Photo-switchable catalysis is a niche area in current catalysis, on which systematic analysis and reviews are still lacking in the scientific literature, yet it offers many intriguing and versatile applications, particularly in organic synthesis...

Sam Foster , Executive Director of Professional Practice, Nursing and Midwifery Council, considers the issues raised for regulators and assessors by the availability of tools such as ChatGPT.

One of the biggest challenges in biotechnology and medical diagnostics is finding extremely sensitive and adaptable biosensors. Since metal-based enzyme-mimetic biocatalysts may lead to biosafety concerns on accumulative toxicity, it is essential to synthesize metal-free enzyme-mimics with optimal biocatalytic activity and superior selectivity. Here, the pyridine-bridged covalent organic frameworks (COFs) with specific oxidase-like (OXD-like) activities as intelligent artificial enzymes for light-augmented biocatalytic sensing of biomarkers are disclosed...

BACKGROUND: Spinal degeneration and vertebral compression fractures are common among the elderly that adversely affect their mobility, quality of life, lung function, and mortality. Assessment of vertebral fractures in chronic obstructive pulmonary disease (COPD) is important due to the high prevalence of osteoporosis and associated vertebral fractures in COPD. PURPOSE: We present new automated methods for (1) segmentation and labelling of individual vertebrae in chest computed tomography (CT) images using deep learning (DL), multi-parametric freeze-and-grow (FG) algorithm, and separation of apparently fused vertebrae using intensity autocorrelation and (2) vertebral deformity fracture detection using computed vertebral height features and parametric computational modelling of an established protocol outlined for trained human experts...

Multiparameter flow cytometry data is visually inspected by expert personnel as part of standard clinical disease diagnosis practice. This is a demanding and costly process, and recent research has demonstrated that it is possible to utilize artificial intelligence (AI) algorithms to assist in the interpretive process. Here we report our examination of three previously published machine learning methods for classification of flow cytometry data and apply these to a B-cell neoplasm dataset to obtain predicted disease subtypes...

INTRODUCTION: Endoleaks represent one of the main complications after endovascular aortic repair (EVAR) and can lead to increased re-intervention rates and secondary rupture. Serial lifelong surveillance is required and traditionally involves cross-sectional imaging with manual axial measurements. Artificial intelligence (AI)-based imaging analysis has been developed and may provide a more precise and faster assessment. This study aims to evaluate the ability of an AI-based software to assess post-EVAR morphological changes over time, detect endoleaks, and associate them with EVAR-related adverse events...

Artificial intelligence (AI) technologies are poised to become an increasingly important part of education in the anatomical sciences. OpenAI has also introduced generative pretrained transformers (GPTs), which are customizable versions of the standard ChatGPT application. There is little research that has explored the potential of GPTs to serve as intelligent tutoring systems for learning the anatomical sciences. The objective of this study was to describe the design and explore the performance of AnatomyGPT, a customized artificial intelligence application intended for anatomical sciences education...