AIMC Topic: COVID-19

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Fuel-Free Rolosense: Viral Sensing Using Diffusional Particle Tracking.

ACS sensors
High-sensitivity viral diagnostics typically use PCR to detect and amplify viral nucleic acids which requires fluorescence reporters, enzymatic amplification, specialized equipment and can be time-consuming. In this work, we describe fuel-free (FF) R...

Designing for Patient-Centered Care and Equity in Virtual Hospital-at-Home Models: Quality Improvement Initiative Using Experience-Based Co-Design.

JMIR human factors
BACKGROUND: The rapid expansion of virtual care during COVID-19 accelerated the development of virtual hospital-at-home models, which deliver hospital-level care in patients' homes through remote monitoring, virtual communication, and in-person suppo...

Delineating SARS-CoV-2 spike protein and antibodies interaction interfaces via siamese neural networks: A geometric and image-based analysis.

PloS one
The analysis of molecular interactions between antigens and antibodies is crucial for understanding the immunological mechanisms underlying the immune response and for developing effective therapies against various diseases. In this context, the abil...

Mapping inequities in global vaccine sentiment research.

BMJ global health
INTRODUCTION: Negative public sentiment towards vaccination (PSV) poses significant challenges to the effectiveness of immunisation programmes, with dramatic effects on morbidity and mortality for vaccine-preventable diseases. Yet, health research is...

Artificial intelligence for arterial blood gas interpretation.

Clinica chimica acta; international journal of clinical chemistry
Arterial blood gas (ABG) analysis is a fundamental diagnostic tool in clinical medicine, offering critical insights into a patient's respiratory and metabolic status. However, interpreting ABG results can be complex and time-sensitive, necessitating ...

Vaccination at a crossroad: science, politics and public trust.

Swiss medical weekly
Vaccine hesitancy threatens to erode one of medicine's greatest achievements. Recent measles outbreaks in Europe and the United States illustrate the consequences of declining confidence. At the centre lies misinformation, amplified through digital n...

Predicting COVID-19 patient recovery or mortality using deep neural decision tree and forest.

BMC research notes
OBJECTIVE: Identifying patients at high risk of mortality is crucial for emergency physicians to allocate hospital resources effectively, particularly in regions with limited medical services. This need becomes even more pressing during global health...

Improving outbreak forecasts through model augmentation.

Proceedings of the National Academy of Sciences of the United States of America
Accurate forecasts of disease outbreaks are critical for effective public health responses, management of healthcare surge capacity, and communication of public risk. There are a growing number of powerful forecasting methods that fall into two broad...

AI-Enhanced Lateral Flow Assay Enables 3-Minute Quantitative Detection with Laboratory-Grade Accuracy.

Analytical chemistry
Lateral flow immunoassay (LFA) remains one of the most widely used point-of-care testing (POCT) platforms for disease diagnosis, food safety assessment, and environmental monitoring. However, traditional LFAs typically require up to 30 min and offer ...

Mass spectrometry combined with machine learning identifies novel protein signatures as demonstrated with multisystem inflammatory syndrome in children.

Scientific reports
Rapid and accurate diagnosis of emerging inflammatory illnesses is challenging due to overlapping clinical features with existing conditions. We demonstrate an approach that integrates proteomic analysis with machine learning to identify diagnostic p...