Surveys

Risk Prediction Models for Contrast-associated Acute Kidney Injury After Percutaneous Coronary Intervention: A Systematic Review.

The aim of this review was to systematically review published studies on risk prediction models for contrast-associated acute kidney injury (CA-AKI) in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI). We searched PubMed, Embase, Web of Science, Scopus, Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Chi...

Machine learning for ammonia volatilization prediction and slurry application management.

Anthropogenic ammonia emissions primarily originate from agriculture, especially field fertilization. These emissions represent nitrogen loss for farmers and contribute to air pollution, posing risks to human health and the environment. Estimating ammonia emissions is crucial for national inventories and policy-making. Various models exist for predicting emissions, including mechanistic, empirical...

Evaluating and mitigating bias in AI-based medical text generation.

Artificial intelligence (AI) systems, particularly those based on deep learning models, have increasingly achieved expert-level performance in medical...

Machine learning modeling and response surface methodology driven antioxidant and anticancer activities of chitosan nanoparticle-mediated extracts of Bacopa monnieri.

This study investigates the potential of chitosan nanoparticles (CNPs) in enhancing the bioavailability and efficacy of Bacopa monnieri extracts, know...

Machine learning modeling and multi objective optimization of artificial detrusor.

To address the problem of obtaining optimal design parameters for existing artificial detrusors using single-objective optimization methods, this rese...

Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic.

Suicide causes over 700,000 deaths annually worldwide. Mental disorders are closely linked to suicidal ideation, but predicting suicide remains comple...

Confidence interval forecasting model of small watershed flood based on compound recurrent neural networks and Bayesian.

Flood forecasting exhibits rapid fluctuations, water level forecasting shows great uncertainty and inaccuracy in small watersheds, and the reliability...

From marker to markerless: Validating DeepLabCut for 2D sagittal plane gait analysis in adults and newly walking toddlers.

The use of 3D marker-based motion analysis systems is considered the gold standard for tracking limb movements. However, these systems are expensive, ...

Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs.

The automated processing of Electronic Health Records (EHRs) poses a significant challenge due to their unstructured nature, rich in valuable, yet dis...

Artificial intelligence in key pricing, reimbursement, and market access (PRMA) processes: better, faster, cheaper-can you really pick two?

The rapid evolution of large language models (LLMs) and machine learning (ML) presents both significant opportunities and challenges for market access...

Enhancing the Predictive Performance of Molecularly Imprinted Polymer-Based Electrochemical Sensors Using a Stacking Regressor Ensemble of Machine Learning Models.

The performance of electrochemical sensors is influenced by various factors. To enhance the effectiveness of these sensors, it is crucial to find the ...

Surrogate modeling of electrospun PVA/PLA nanofibers using artificial neural network for biomedical applications.

Blending poly (lactic acid) (PLA) with poly (vinyl alcohol) (PVA) improves the strength and hydrophilicity of nanofibers, making them suitable for bio...

The satisfaction of ecological environment in sports public services by artificial intelligence and big data.

In order to gain a more accurate understanding and enhance the relationship between the fitness ecological environment and artificial intelligence (AI...

Adaptive neural fault-tolerant tracking control for state-constrained systems subject to multiple power drift faults.

The adaptive neural fault-tolerant control (FTC) for state-constrained systems containing novel sensor and actuator faults is investigated in this art...

Detecting implicit biases of large language models with Bayesian hypothesis testing.

Despite the remarkable performance of large language models (LLMs), such as generative pre-trained Transformers (GPTs), across various tasks, they oft...

Semantic signals in self-reference: The detection and prediction of depressive symptoms from the daily diary entries of a sample with major depressive disorder.

Individuals with major depressive disorder (MDD) experience fewer positive and more negative emotions and use fewer positive words to describe themsel...

The promise and challenges of computer mouse trajectories in DMHIs - A feasibility study on pre-treatment dropout predictions.

With the impetus of Digital Mental Health Interventions (DMHIs), complex data can be leveraged to improve and personalize mental health care. However,...

The Role of Artificial Intelligence in the Diagnosis and Management of Rheumatoid Arthritis.

Artificial intelligence has emerged as a transformative tool in healthcare, offering capabilities such as early diagnosis, personalised treatment, an...

AI-imputed and crowdsourced price data show strong agreement with traditional price surveys in data-scarce environments.

Continuous access to up-to-date food price data is crucial for monitoring food security and responding swiftly to emerging risks. However, in many foo...

Parental Perception on Usage of AI Chatbot to Understand Paediatric Otorhinolaryngology Condition: A Survey.

UNLABELLED: Artificial intelligence (AI) chatbots such as ChatGPT have the potential to assist parents and caregivers in understanding their child's g...