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Pandemics

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Next-Generation Teleophthalmology: AI-enabled Quality Assessment Aiding Remote Smartphone-based Consultation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Blindness and other eye diseases are a global health concern, particularly in low- and middle-income countries like India. In this regard, during the COVID-19 pandemic, teleophthalmology became a lifeline, and the Grabi attachment for smartphone-base...

Time-varying compartmental models with neural networks for pandemic infection forecasting.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The emergence and spread of deadly pandemics has repeatedly occurred throughout history, causing widespread infections and life loss. Forecasting the progression of pandemics is crucial for decision-makers to achieve its mitigation. This predictive t...

Cough Classification of Unknown Emerging Respiratory Disease with Federated Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Artificial intelligence offers great potential to address the need for rapid diagnostic testing in pandemic scenarios. Concerns about security and privacy, however, complicate the collection of large representative medical data. Federated Learning (F...

Leveraging artificial intelligence to assess the impact of COVID-19 on the teacher-student relationship in higher education.

PloS one
The teacher-student relationship has far-reaching implications for educational outcomes at the tertiary level. Teachers contribute to students' success in various ways, including academic support, career counseling, personal mentoring, etc., that hel...

AI-driven health analysis for emerging respiratory diseases: A case study of Yemen patients using COVID-19 data.

Mathematical biosciences and engineering : MBE
In low-income and resource-limited countries, distinguishing COVID-19 from other respiratory diseases is challenging due to similar symptoms and the prevalence of comorbidities. In Yemen, acute comorbidities further complicate the differentiation bet...

An ensemble approach improves the prediction of the COVID-19 pandemic in South Korea.

Journal of global health
BACKGROUND: Modelling can contribute to disease prevention and control strategies. Accurate predictions of future cases and mortality rates were essential for establishing appropriate policies during the COVID-19 pandemic. However, no single model yi...

Estimating the causal impact of non-pharmaceutical interventions on COVID-19 spread in seven EU countries via machine learning.

Scientific reports
During the COVID-19 pandemic, Non-Pharmaceutical Interventions (NPIs) were imposed all over Europe with the intent to reduce infection spread. However, reports on the effectiveness of those measures across different European countries are inconclusiv...

Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic.

BMC medicine
BACKGROUND: Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiable factors contributing to vaccine hesitancy is crucial for developing targeted interventions to incr...

Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.

Journal of medical Internet research
BACKGROUND: While the COVID-19 pandemic has induced massive discussion of available medications on social media, traditional studies focused only on limited aspects, such as public opinions, and endured reporting biases, inefficiency, and long collec...

Machine learning in point-of-care testing: innovations, challenges, and opportunities.

Nature communications
The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine learning (ML) into decentralized, rapid, and accessible sensor platforms for point-of-care testing (...