Flu & URI

Machine learning-assisted sensing platform for simultaneous and visual detection of tetracycline hydrochloride and ofloxacin.

Antibiotics are essential in modern medicine; however, their overuse and improper disposal have caused significant environmental contamination, which impacts aquatic systems, food chains, and ecosystems while posing serious risks to human health. Current antibiotic detection methods are typically confined to laboratories and require professional expertise, creating a gap for portable sensors suita...

Machine Learning-Enhanced Clinical Decision Support for Diagnosing Sinusitis With Nasal Endoscopy.

BACKGROUND: Sinusitis is a prevalent disease for which nasal endoscopy (NE) is an optimal diagnostic modality. However, NE accuracy is limited by inter-operator variability in landmark identification and localization of mucus that is necessary for sinusitis diagnosis. We sought to develop a novel multi-class machine learning (ML) framework that detects anatomical landmarks and structures for sinus...

Cervical cancer diagnostics: non-coding RNAs and biosensors to AI-derived methods.

Cervical cancer ranks fourth in terms of cancer mortality among women. The most important risk factor for cervical cancer is infection with HPV 16 and...

When AI Joins the Social Media Conversation: Exploring the Impact of Simulated AI-Assisted Comments on Health Risk Perceptions and Behaviors.

Misinformation on social media has long been a pressing concern, and its spread is often exacerbated by social endorsement metrics such as likes and s...

Elucidating anti-triple-negative breast cancer mechanisms and mitigating toxicity of Fritillaria thunbergii Miq.: A multi-omics and network pharmacology approach.

ETHNOPHARMACOLOGICAL RELEVANCE: Fritillaria thunbergii Miq. (Zhebeimu, ZBM) is traditionally recognized in Chinese medicine for its effects of clearin...

AI-driven diagnosis of Lassa fever: Evidence from Nigerian clinical records.

BACKGROUND: Neglected Tropical Diseases (NTDs), particularly Lassa fever, remain a significant public health challenge in Nigeria, often presenting wi...

Cancer vaccines: Discovery, development, and challenges for clinical translation.

Cancer vaccines stimulate antitumor immunity by delivering tumor antigens and, in recent years, have emerged as a promising therapeutic strategy again...

QDCRNet: Quantum dilated convolutional recurrent network for virus detection using gene expression data.

Viral Infections cause several common human illnesses, like the common cold, flu, mouth blisters, and chickenpox. However, numerous viruses, including...

Crafting an innovative one health-aligned machine learning framework for neglected tropical diseases elimination.

INTRODUCTION: Strategic investment in new interventions is crucial for controlling and eliminating NTDs. However, selecting the optimal intervention c...

Ethical Implications of Artificial Intelligence in Vaccine Equity: Protocol for Exploring Vaccine Distribution Planning and Scheduling in Pandemics in Low- and Middle-Income Countries.

BACKGROUND: The COVID-19 pandemic highlighted significant disparities in vaccine distribution, particularly in low- and middle-income countries (LMICs...

Prediction and characterisation of the human B cell response to a heterologous two-dose Ebola vaccine.

Ebola virus disease (EVD) outbreaks are increasing, posing significant threats to affected communities. Effective outbreak management depends on prote...

Predicting SARS-CoV-2-specific CD4 and CD8 T-cell responses elicited by inactivated vaccines in healthy adults using machine learning models.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlights the importance of monitoring immune response...

Deep Learning-Enhanced Hand-Driven Spatial Encoding Microfluidics for Multiplexed Molecular Testing at Home.

The frequent global outbreaks of viral infectious diseases have significantly heightened the urgent demand for molecular testing at home. However, the...

Machine learning approaches to dissect hybrid and vaccine-induced immunity.

BACKGROUND: The spread of SARS-CoV-2 Omicron variant and its subvariants, highly transmissible but responsible of milder disease, has increased unrepo...

Predictive models of influenza A virus lethal disease yield insights from ferret respiratory tract and brain tissues.

Collection of systemic tissues from influenza A virus (IAV)-infected ferrets at a fixed timepoint post-inoculation represents a frequent component of ...

Discrimination of Dengue Diseases in Children Using Surface-Enhanced Raman Spectroscopy Coupled with Machine Learning Approaches.

This study introduces a novel approach to dengue diagnostics by leveraging surface-enhanced Raman spectroscopy (SERS) coupled to machine learning. Thi...

Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds.

BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD), a progressively worsening respiratory condition, severely impacts patient qual...

Automated identification of spotted-fever tick vectors using convolutional neural networks.

Ticks are key ectoparasites for the One Health approach, as they are vectors of pathogens that infect humans, domestic and wild animals. The bacteria ...

Deep learning-driven insights into the transmission dynamics of hepatitis B virus with treatment.

Viral infections have spread globally, profoundly affecting social and economic aspects of life and causing widespread suffering. Infection caused by ...

Development of machine learning prediction models for systemic inflammatory response following controlled exposure to a live attenuated influenza vaccine in healthy adults using multimodal wearable biosensors in Canada: a single-centre, prospective controlled trial.

BACKGROUND: Presymptomatic or asymptomatic immune system signals and subclinical physiological changes might provide a more objective measure of early...