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Sexually Transmitted Diseases

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Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier.

Journal of medical systems
Cervical cancer is the fourth most communal malignant disease amongst women worldwide. In maximum circumstances, cervical cancer indications are not perceptible at its initial stages. There are a proportion of features that intensify the threat of em...

Using Machine Learning to Identify Predictors of Sexually Transmitted Infections Over Time Among Young People Living With or at Risk for HIV Who Participated in ATN Protocols 147, 148, and 149.

Sexually transmitted diseases
BACKGROUND: Sexually transmitted infections (STIs) among youth aged 12 to 24 years have doubled in the last 13 years, accounting for 50% of STIs nationally. We need to identify predictors of STI among youth in urban HIV epicenters.

Development of a Machine Learning Modeling Tool for Predicting HIV Incidence Using Public Health Data From a County in the Southern United States.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: Advancements in machine learning (ML) have improved the accuracy of models that predict human immunodeficiency virus (HIV) incidence. These models have used electronic medical records and registries. We aim to broaden the application of t...