Interpretable Machine Learning Model for Fungal Infection Prediction: A Real‐World Study
Our study successfully developed and validated a machine learning model based on large‐scale electronic health record data to predict the risk of fungal infections in hospitalized patients. Through a Streamlit‐powered web platform, the model was seamlessly embedded into clinical workflows, completing the full pipeline from model construction to real ...
Jinru Yang +5 more
wiley +1 more source
Excess HIV Infections and Costs Associated With Reductions in HIV Prevention Services in the US.
Sullivan PS +9 more
europepmc +1 more source
What will it take to expand the pre-exposure prophylaxis to prevent new HIV infections in India? [PDF]
Gaur A, Rakhmanina N.
europepmc +1 more source
Correlates of unawareness of HIV status and recency of HIV infections among women living with HIV: findings from population-based surveys in 13 African countries. [PDF]
Mbabazi I +4 more
europepmc +1 more source
Altered Host microRNAomics in HIV Infections: Therapeutic Potentials and Limitations. [PDF]
Santiago MJ +8 more
europepmc +1 more source
New Therapies and Strategies to Curb HIV Infections with a Focus on Macrophages and Reservoirs. [PDF]
Marra M +9 more
europepmc +1 more source
Recent HIV infections and estimated HIV incidence among adolescents from key populations. [PDF]
Zeballos D +8 more
europepmc +1 more source
Correction to: Prevalence of HBV, HCV, and HIV Infections among Patients Undergoing Hemodialysis in Fasa, Iran: A Six-Year Follow-up Study. [PDF]
Shamsdin SA +3 more
europepmc +1 more source
ABSTRACT Sub‐Saharan Africa (SSA) continues to experience a high and uneven disease burden, mainly from HIV/AIDS, tuberculosis, and malaria. As external funding declines, the strategic allocation of domestic public health spending (DPHS) becomes crucial.
Wa Ntita Serge Kabongo, Josue Mbonigaba
wiley +1 more source

