AIMC Topic: COVID-19

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Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.

Scientific reports
Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal clinical records. The motivation stems from the need for timely medical resource allocation, improved ...

Mitochondrial haplogroup A2 is associated with increased COVID-19 mortality in an admixed Brazilian population.

Scientific reports
Mitochondria play a crucial role in cellular respiration and immune responses. Mitochondrial DNA (mtDNA) haplogroups and variants have been associated with various diseases, including COVID-19. This study analyzed complete mtDNA sequences from 467 Br...

Deep learning based knowledge tracing in intelligent tutoring systems.

Scientific reports
The emergence of online education, e.g., intelligent tutoring system (ITS), complements or partially replaces conventional offline education, especially during the COVID-19 pandemic. Knowledge tracing (KT) plays a pivotal role in the intelligent tuto...

Leveraging federated learning and edge computing for pandemic-resilient healthcare.

Scientific reports
The universal demand for the development and deployment of responsive medical infrastructure and damage control techniques, including the application of technology, is the foremost necessity that emerged immediately in the post-pandemic era. Numerous...

Identifying real time surveillance indicators to estimate COVID-19 hospital admissions in Colorado during and after the public health emergency.

Scientific reports
Questions remain about how best to focus surveillance efforts for COVID-19 and other emerging respiratory diseases. We used an archive of COVID-19 data in Colorado from October 2020 to March 2024 to reconstruct seven real-time surveillance indicators...

A textual dataset of de-identified health records in Spanish and Catalan for medical entity recognition and anonymization.

Scientific data
The advancement of clinical natural language processing systems is crucial to exploit the wealth of textual data contained in medical records. Diverse data sources are required in different languages and from different sites to represent global healt...

Human protein interaction networks of ancestral and variant SARS-CoV-2 in organ-specific cells and bodily fluids.

Nature communications
Understanding SARS-CoV-2 human protein-protein interactions (PPIs) and the host response to infection is essential for developing effective COVID-19 antivirals. However, how the ancestral virus and its variants remodel virus-host protein assemblies i...

Lessons learned from RadiologyNET foundation models for transfer learning in medical radiology.

Scientific reports
Deep learning models require large amounts of annotated data, which are hard to obtain in the medical field, as the annotation process is laborious and depends on expert knowledge. This data scarcity hinders a model's ability to generalise effectivel...

In-silico study of approved drugs as potential inhibitors against 3CLpro and other viral proteins of CoVID-19.

PloS one
The global pandemic, due to the emergence of COVID-19, has created a public health crisis. It has a huge morbidity rate that was never comprehended in the recent decades. Despite numerous efforts, potent antiviral drugs are lacking. Repurposing of dr...

Mobile Apps to Prevent Violence Against Women and Girls (VAWG): Systematic App Research and Content Analysis.

JMIR formative research
BACKGROUND: Numerous reviews have explored specific aspects of violence prevention apps, but given the rapid development of new apps, increased violence during COVID-19, and gaps in understanding functionalities and geographical distribution, an upda...