AIMC Topic: HIV Infections
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Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.
Topics in magnetic resonance imaging : TMRI
Jun 28, 2022
OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remar...
A three-methylation-driven gene-based deep learning model for tuberculosis diagnosis in patients with and without human immunodeficiency virus co-infection.
Microbiology and immunology
May 27, 2022
Improved diagnostic tests for tuberculosis (TB) among people with human immunodeficiency virus (HIV) are urgently required. We hypothesized that methylation-driven genes (MDGs) of host blood could be used to diagnose patients co-infected with HIV/TB....
Switching to a NRTI-free 2 drug regimen (2DR) -a sub-analysis of the 48 weeks DUALIS study on metabolic and renal changes.
HIV research & clinical practice
Mar 2, 2022
Switching from a three-drug regimen (3DR: boosted darunavir [bDRV] and two nucleoside reverse transcriptase inhibitors [NRTIs]) to a two-drug regimen (2DR: bDRV and dolutegravir [DTG]) demonstrated non-inferiority with regard to viral suppression in...
Different features identified by machine learning associated with the HIV compartmentalization in semen.
Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Jan 23, 2022
Genetic compartmentalization in semen has been observed in previous studies. However, genetic signatures associated with compartmentalization in semen are only beginning to be explored. A total of 2071 partial HIV env sequences for paired blood and s...
Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm.
CPT: pharmacometrics & systems pharmacology
Dec 9, 2021
Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine-learning tec...
Long-term safety and efficacy of rilpivirine in combination with nucleoside/nucleotide reverse transcriptase inhibitors in HIV-1 infected patients: 336-week rollover study of phase 2b and 3 clinical studies.
Antiviral therapy
Nov 26, 2021
BACKGROUND: To evaluate the long-term safety and efficacy of rilpivirine (RPV), a non-nucleoside reverse transcriptase inhibitor (NNRTI), in combination with nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) in human immunodeficiency vir...
Rilpivirine plus cobicistat-boosted darunavir as alternative to standard three-drug therapy in HIV-infected, virologically suppressed subjects: Final results of the PROBE 2 trial.
Antiviral therapy
Oct 27, 2021
BACKGROUND: Primary analysis at 24 weeks showed that switching to rilpivirine plus darunavir/cobicistat was non-inferior to continuing a standard three-drug antiretroviral regimen in virologically suppressed people with HIV. We present efficacy and s...
Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.
PLoS computational biology
Sep 22, 2021
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This tech...
Using machine learning and big data to explore the drug resistance landscape in HIV.
PLoS computational biology
Aug 26, 2021
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...
Deep learning of HIV field-based rapid tests.
Nature medicine
Jun 17, 2021
Although deep learning algorithms show increasing promise for disease diagnosis, their use with rapid diagnostic tests performed in the field has not been extensively tested. Here we use deep learning to classify images of rapid human immunodeficienc...
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