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Predict patient deterioration in hospital's general ward
(2020)
Increasing amount of patient monitoring data is available in hospitals in an electronic format. Patient data is mostly available from hospital departments which provide intensive treatment, but wireless and wearable sensors ...
Predicting fine particulate matter levels in Finnish buildings
(2019)
Fine particulate matter (PM 2.5 ) is considered one of the most harmful air pollutants. While
a large proportion of the particles is originating from outdoor sources, people are mostly
exposed while indoors. Predicting ...
Examination of air pollutant concentrations in Smart City Helsinki using data exploration and deep learning methods
(2021)
Air quality has become a major concern for most of the cities around Europe due to rapid urbanization and industrialization. Smart City is an initiative to solve such problems by integrating information and communication ...
Analysing Patterns In Depression-Related Web Searches Via Google Trends A case study in Finland during the 2015-2021 period
(2022)
Considering high level of internet usage in Finland and popularity of Google Search Engine, in this research, we scrape Google Trend time series data for six years from 2015 to 2021 for depression-related-terms in Finland ...
Explainability of time series models
(2022)
The lack of interpretability of machine learning models is a drawback of their use. To better understand how the model works, how data affects its performance, how the model could be improved, and to gain trust in the ...
Car sales analysis in the Nordic Countries
(2023)
Sales forecasting is an essential component of business intelligence and, artificial intelligence and predictive analytics are now essential tools for companies to predict market trends and forecast sales volumes.
In ...
The impact of COVID-19 on machine learning models in a commercial aviation use case
(2022)
The COVID-19 pandemic has led to unforeseen changes in the world. These changes have had a serious impact on many machine learning models. These models rely on historic data to generate forecasts and make decisions. The ...