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Creating prediction models for cervical cancer forecasting
The aim of this bachelor’s thesis is to create prediction models for cervical cancer (ICD-10 C53) and pre-cancerous condition (ICD-10 R87.613) forecasting. The analysis is based on health data of 10% of Estonian population that was provided by STACC OÜ. The thesis gives an overview on cervical cancer, shows which prediction models were created using different machine learning algorithms, evaluates their performance, and gives an overview on factors that might affect risk of getting the diseases.
- University of Tartu Estonia
prediction model, machine learning, risk model, riskimudel, logistic regression, logistiline regressioon, masinõpe, ennustamismudel
prediction model, machine learning, risk model, riskimudel, logistic regression, logistiline regressioon, masinõpe, ennustamismudel
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average Powered byBIP!

The aim of this bachelor’s thesis is to create prediction models for cervical cancer (ICD-10 C53) and pre-cancerous condition (ICD-10 R87.613) forecasting. The analysis is based on health data of 10% of Estonian population that was provided by STACC OÜ. The thesis gives an overview on cervical cancer, shows which prediction models were created using different machine learning algorithms, evaluates their performance, and gives an overview on factors that might affect risk of getting the diseases.