Flu & URI

Effect of esketamine on the EC of remifentanil for suppression of choking cough during extubation.

Choking cough during awakening from anesthesia is common (15%-94%) and can cause severe discomfort and complications, especially in neck surgery. This study compared the median effective concentration (EC) of remifentanil combined with esketamine versus remifentanil alone for suppressing cough during extubation in male patients undergoing anterior cervical spine surgery. Group E received 0.25 mg/k...

A vaccine chatbot intervention for parents to improve HPV vaccination uptake among middle school girls: a cluster randomized trial.

Conversational artificial intelligence, in the form of chatbots powered by large language models, offers a new approach to facilitating human-like interactions, yet its efficacy in enhancing vaccination uptake remains under-investigated. This study assesses the effectiveness of a vaccine chatbot in improving human papillomavirus (HPV) vaccination among female middle school students aged 12-15 year...

Safety assessment of the ethanolic extract of Siparuna guianensis: Cell viability, molecular risk predictions and toxicity risk for acute and sub-chronic oral ingestion.

ETHNOPHARMACOLOGICAL RELEVANCE: The species Siparuna guianensis Aublet (family Siparunaceae) is traditionally used by indigenous peoples and riverine ...

Using deep learning artificial intelligence for sex identification and taxonomy of sand fly species.

Sandflies are vectors for several tropical diseases such as leishmaniasis, bartonellosis, and sandfly fever. Moreover, sandflies exhibit species-speci...

A hybrid long short-term memory-convolutional neural network multi-stream deep learning model with Convolutional Block Attention Module incorporated for monkeypox detection.

BackgroundMonkeypox (mpox) is a zoonotic infectious disease caused by the mpox virus and characterized by painful body lesions, fever, headaches, and ...

Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study.

BACKGROUND: Pertussis is a highly contagious respiratory disease. Even though vaccination has reduced the incidence, cases have resurfaced in certain ...

Explainable AI for Symptom-Based Detection of Monkeypox: a machine learning approach.

BACKGROUND: Monkeypox, a viral zoonotic disease, is an emerging global health concern, with rising incidence and outbreaks extending beyond its endemi...

Preliminary evaluation of ChatGPT model iterations in emergency department diagnostics.

Large language model chatbots such as ChatGPT have shown the potential in assisting health professionals in emergency departments (EDs). However, the ...

Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models.

OBJECTIVE: The rapid evolution of the COVID-19 virus has led to the development of different vaccine shots, each designed to combat specific variants ...

Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects.

BACKGROUND: Dengue fever is a mosquito-borne viral disease that poses significant health risks and socioeconomic challenges in Brazil, necessitating a...

Unraveling the power of NAP-CNB's machine learning-enhanced tumor neoantigen prediction.

In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) ...

Development and validation of a machine learning model for predicting intrapartum fever using pre-labor analgesia clinical indicators: a multicenter retrospective study.

BACKGROUND: Labor anesthesia is commonly used for pain relief during labor, but it can increase the risk of intrapartum fever. Currently, there are no...

Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms.

To retrospectively analyze the clinical characteristics of pediatric scrub typhus (ST) with meningoencephalitis (STME) and to construct and validate p...

Edge Computing System for Automatic Detection of Chronic Respiratory Diseases Using Audio Analysis.

Chronic respiratory diseases affect people worldwide, but conventional diagnostic methods may not be accessible in remote locations far from populatio...

CT Differentiation and Prognostic Modeling in COVID-19 and Influenza A Pneumonia.

RATIONALE AND OBJECTIVES: This study aimed to compare CT features of COVID-19 and Influenza A pneumonia, develop a diagnostic differential model, and ...

CEL: A Continual Learning Model for Disease Outbreak Prediction by Leveraging Domain Adaptation via Elastic Weight Consolidation.

Continual learning is the ability of a model to learn over time without forgetting previous knowledge. Therefore, adapting new data in dynamic fields ...

Toward a rapid, sensitive, user-friendly, field-deployable artificial intelligence tool for enhancing African swine fever diagnosis and reporting.

OBJECTIVE: African swine fever (ASF) is a lethal and highly contagious transboundary animal disease with the potential for rapid international spread....

OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune system are well established. This study aims to develop...

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging a...

Machine learning for early diagnosis of Kawasaki disease in acute febrile children: retrospective cross-sectional study in China.

Early diagnosis of Kawasaki disease (KD) allows timely treatment to be initiated, thereby preventing coronary artery aneurysms in children. However, i...