AIMC Topic: AIDS-Related Opportunistic Infections

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Predictive survival modelings for HIV-related cryptococcosis: comparing machine learning approaches.

Frontiers in cellular and infection microbiology
INTRODUCTION: HIV-associated cryptococcosis is marked by unpredictable disease trajectories and persistently high mortality rates worldwide. Although improved risk stratification and tailored clinical management are urgently needed to enhance patient...

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.

PloS one
Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our ob...

A Machine Learning Model for Diagnosing Opportunistic Infections in HIV Patients: Broad Applicability Across Infection Types.

Journal of cellular and molecular medicine
Opportunistic infections (OIs) are the leading cause of hospitalisation and mortality among Human Immunodeficiency Virus-infected (HIV-infected) patients. The diverse pathogen types and intricate clinical manifestations associated present a formidabl...

[Cerebral cryptococcosis and immune reconstitution inflammatory syndrome. Case report].

Revista medica de Chile
We report a 45-year-old male with AIDS who had a Cryptococcus neoformans central nervous system infection. He was treated with amphotericin B deoxycholate subsequently changed to voriconazole due to systemic toxicity of the former. Plasma levels of v...