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Imbalanced class distribution and performance evaluation metrics: A systematic review of prediction accuracy for determining model performance in healthcare …
Focus on predictive algorithm and its performance evaluation is extensively covered in most
research studies to determine best or appropriate predictive model with Optimum prediction …
research studies to determine best or appropriate predictive model with Optimum prediction …
COVID-19 prediction using black-box based Pearson correlation approach
The novel coronavirus (COVID-19), also known as SARS-CoV-2, is a highly contagious
respiratory disease that first emerged in Wuhan, China in 2019 and has since become a …
respiratory disease that first emerged in Wuhan, China in 2019 and has since become a …
Introduction to the special issue ''Environmental impacts of COVID-19 pandemic”
S Gautam, ARK Gollakota - Gondwana Research, 2022 - pmc.ncbi.nlm.nih.gov
COVID-19 (Coronavirus Disease–2019) is an infectious disease identified in late December
2019 in the Wuhan city of China and well known to the world as WHO (World Health …
2019 in the Wuhan city of China and well known to the world as WHO (World Health …
[HTML][HTML] The Impact of High-Density Urban Wind Environments on the Distribution of COVID-19 Based on Machine Learning: A Case Study of Macau
The COVID-19 epidemic has become a global challenge, and the urban wind environment,
as an important part of urban spaces, may play a key role in the spread of the virus …
as an important part of urban spaces, may play a key role in the spread of the virus …
Deep learning methods for scientific and industrial research
Deep learning (DL) is a very powerful computational tool for various applications in scientific
and industrial research which can be real-time implemented for societal benefits. Several …
and industrial research which can be real-time implemented for societal benefits. Several …
Revisiting the joint effect of temperature and relative humidity on airborne mold and bacteria concentration in indoor environment: A machine learning approach
D Kim, D Shin, D Kim, B Kwon, C Min… - Building and …, 2025 - Elsevier
Abstracts Exposure to airborne bioaerosols, such as bacteria and fungi, presents significant
health risks, especially for vulnerable populations like children, the elderly, and those with …
health risks, especially for vulnerable populations like children, the elderly, and those with …
Study on the spatial decomposition of the infection probability of COVID-19
L Liu - Scientific Reports, 2023 - nature.com
In the course of our observations of the transmission of COVID-19 around the world, we
perceived substantial concern about imported cases versus cases of local transmission. This …
perceived substantial concern about imported cases versus cases of local transmission. This …
COVID-19 vaccine prediction based on an interpretable CNN-LSTM model with three-stage feature engineering
Purpose Vaccine supply planning remains a critical and challenging issue for develo**
countries due to the limited resources and fluctuating vaccine demand, reflected by the …
countries due to the limited resources and fluctuating vaccine demand, reflected by the …
Predictive analysis of COVID-19 occurrence and vaccination impacts across the 50 US states
Objective This study aimed to outline a machine learning model to assess the effectiveness
of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was …
of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was …
Forecasting daily COVID-19 cases with gradient boosted regression trees and other methods: evidence from US cities
Introduction There is a vast literature on the performance of different short-term forecasting
models for country specific COVID-19 cases, but much less research with respect to city …
models for country specific COVID-19 cases, but much less research with respect to city …