HIV/AIDS

m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.

N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pi...

Lower limb rehabilitation robotics: The current understanding and technology.

BACKGROUND: With the increasing rate of ambulatory disabilities and rise in the elderly population, ...

Dermoscopic Features of Giant Molluscum Contagiosum in a Patient with Acquired Immunodeficiency Syndrome.

Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple ...

State-of-the-Art Traditional to the Machine- and Deep-Learning-Based Skull Stripping Techniques, Models, and Algorithms.

Several neuroimaging processing applications consider skull stripping as a crucial pre-processing st...

[Prevalence of transmitted drug resistance in HIV-infected treatment-naive patients in Chile].

BACKGROUND: Transmitted drug resistance (TDR) occurs in patients with HIV infection who are not expo...

Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images.

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an exis...

Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV.

BACKGROUND: Frailty is an important clinical concern for the aging population of people living with ...

[Determination of 18 pesticide residues in environmental water by solid phase extraction-ultra performance liquid chromatography-tandem mass spectrometry].

A method was developed for the simultaneous determination of 18 pesticide residues in environmental ...

Computer-aided diagnosis in the era of deep learning.

Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses...

Machine learning techniques for biomedical image segmentation: An overview of technical aspects and introduction to state-of-art applications.

In recent years, significant progress has been made in developing more accurate and efficient machin...

Artificial Intelligence and Machine Learning for HIV Prevention: Emerging Approaches to Ending the Epidemic.

PURPOSE OF REVIEW: We review applications of artificial intelligence (AI), including machine learnin...

Advancing PICO element detection in biomedical text via deep neural networks.

MOTIVATION: In evidence-based medicine, defining a clinical question in terms of the specific patien...

Machine-learning classification of neurocognitive performance in children with perinatal HIV initiating de novo antiretroviral therapy.

OBJECTIVE: To develop a predictive model of neurocognitive trajectories in children with perinatal H...

Super learner analysis of real-time electronically monitored adherence to antiretroviral therapy under constrained optimization and comparison to non-differentiated care approaches for persons living with HIV in rural Uganda.

INTRODUCTION: Real-time electronic adherence monitoring (EAM) systems could inform on-going risk ass...

Evaluating the Effect of Dexmedetomidine on Hemodynamic Status of Patients with Septic Shock Admitted to Intensive Care Unit: A Single-Blind Randomized Controlled Trial.

Septic shock, known as the most severe complication of sepsis, is a serious medical condition that c...

Revisiting CRISPR/Cas-mediated crop improvement: Special focus on nutrition.

Genome editing (GE) technology has emerged as a multifaceted strategy that instantaneously popularis...

Deep Learning in Medical Image Analysis.

Deep learning is the state-of-the-art machine learning approach. The success of deep learning in man...

Advancing the state of the art in automatic extraction of adverse drug events from narratives.

PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation in Digital Pathology.

The diagnosis of disease often requires analysis of a biopsy. Many diagnoses depend not only on the ...

Deep Learning Analysis of Cerebral Blood Flow to Identify Cognitive Impairment and Frailty in Persons Living With HIV.

BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairme...

Network context matters: graph convolutional network model over social networks improves the detection of unknown HIV infections among young men who have sex with men.

OBJECTIVE: HIV infection risk can be estimated based on not only individual features but also social...