Publications by authors named "E Kalluci"

The article "Correlation between COVID-19 and air pollution: the effects of PM2.5 and PM10 on COVID-19 outcomes", by E. Kalluçi, E.

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Background: The human microbiome, consisting of diverse bacte-rial, fungal, protozoan and viral species, exerts a profound influence on various physiological processes and disease susceptibility. However, the complexity of microbiome data has presented significant challenges in the analysis and interpretation of these intricate datasets, leading to the development of specialized software that employs machine learning algorithms for these aims.

Methods: In this paper, we analyze raw data taken from 16S rRNA gene sequencing from three studies, including stool samples from healthy control, patients with adenoma, and patients with colorectal cancer.

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Objective: Given its effects on long-term illnesses, like heart problems and diabetes, air pollution may be among the reasons that led COVID-19 to get worse and kill a larger number of people. Experiments have shown that breathing in polluted air weakens the immune system, making it easier for viruses to enter the body and grow. Viruses may be able to survive in the air by interacting in complex ways with particles and gases.

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Article Synopsis
  • The human microbiome is a key area of research for understanding health, but analyzing its complex data is challenging.
  • Machine learning (ML) algorithms are being developed to help process this data, uncover patterns, and create predictive models.
  • This review catalogs ML-based software tools for microbiome analysis, providing insights, usage examples, and highlighting areas that need improvement for both developers and users.
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Background: Infectious diseases are disorders caused by microorganisms such as bacteria, viruses, fungi, or parasites. Many organisms live in and on our bodies. They are normally harmless or even helpful.

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