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Outputs (6)

Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences (2024)
Journal Article
Zarrin, Z., Hamidi, O., Amini, P., & Maryanaji, Z. (in press). Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences. BMC Research Notes, 17(1), Article 221. https://doi.org/10.1186/s13104-024-06878-6

Objective: This study delves into the impact of urban meteorological elements—specifically, air temperature, relative humidity, and atmospheric pressure—on water consumption in Kamyaran city. Data on urban water consumption, temperature (in Celsius),... Read More about Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences.

A Comprehensive Performance Comparison Study of Various Statistical Models that Accommodate Challenges of the Gut Microbiome Data (2024)
Journal Article
Hajihosseini, M., Amini, P., Saidi-Mehrabad, A., Hajizadeh, N., Kozyrskyj, A. L., & Dinu, I. (in press). A Comprehensive Performance Comparison Study of Various Statistical Models that Accommodate Challenges of the Gut Microbiome Data. Statistics in Biosciences, https://doi.org/10.1007/s12561-024-09435-8

The human gut microbiome refers to trillions of symbiotic bacteria that colonize the human gut after birth, having an essential role in maintaining human health. Various factors can influence the human microbiome, delaying normal gut microbiota’s mat... Read More about A Comprehensive Performance Comparison Study of Various Statistical Models that Accommodate Challenges of the Gut Microbiome Data.

Social determinants of spatial inequalities in COVID-19 outcomes across England: A multiscale geographically weighted regression analysis. (2024)
Journal Article
Khedmati Morasae, E., Derbyshire, D. W., Amini, P., & Ebrahimi, T. (2024). Social determinants of spatial inequalities in COVID-19 outcomes across England: A multiscale geographically weighted regression analysis. SSM - Population Health, 25, Article 101621. https://doi.org/10.1016/j.ssmph.2024.101621

A variety of factors are associated with greater COVID-19 morbidity or mortality, due to how these factors influence exposure to (in the case of morbidity) or severity of (in the case of mortality) COVID-19 infections. We use multiscale geographicall... Read More about Social determinants of spatial inequalities in COVID-19 outcomes across England: A multiscale geographically weighted regression analysis..

Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method (2024)
Journal Article
Amoori, N., Cheraghian, B., Amini, P., & Alavi, S. M. (2024). Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method. Medical Journal of the Islamic Republic of Iran, 38(1), 21-27. https://doi.org/10.47176/mjiri.38.5

BackgroundTuberculosis is a principal public health issue. Reducing and controlling tuberculosis did not result in the expected success despite implementing effective preventive and therapeutic programs, one of the reasons for which is the delay in d... Read More about Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method.

Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis. (2023)
Journal Article
Afshar, S., Leili, T., Amini, P., & Dinu, I. (2023). Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis. Heliyon, 9(8), Article e18869. https://doi.org/10.1016/j.heliyon.2023.e18869

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify no... Read More about Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis..

Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity. (2023)
Journal Article
Amini, P., Hajihosseini, M., Pyne, S., & Dinu, I. (2023). Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity. Frontiers in Cell and Developmental Biology, 11, Article 1065586. https://doi.org/10.3389/fcell.2023.1065586

Background: The impact of gene-sets on a spatial phenotype is not necessarily uniform across different locations of cancer tissue. This study introduces a computational platform, GWLCT, for combining gene set analysis with spatial data modeling to pr... Read More about Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity..