Infectious Disease

HIV/AIDS

Latest AI and machine learning research in hiv/aids for healthcare professionals.

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Showing 379-399 of 3,306 articles
Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review.

OBJECTIVES: To identify studies promoting the use of artificial intelligence (AI) or automation with...

Distillation of multi-class cervical lesion cell detection via synthesis-aided pre-training and patch-level feature alignment.

Automated detection of cervical abnormal cells from Thin-prep cytologic test (TCT) images is crucial...

A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.

Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstructi...

What Are Humans Doing in the Loop? Co-Reasoning and Practical Judgment When Using Machine Learning-Driven Decision Aids.

Within the ethical debate on Machine Learning-driven decision support systems (ML_CDSS), notions suc...

Prediction of candidemia with machine learning techniques: state of the art.

In this narrative review, we discuss studies assessing the use of machine learning (ML) models for t...

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, a...

Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review.

PURPOSE OF REVIEW: Artificial intelligence (AI) is transforming electrocardiography (ECG) interpreta...

Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning.

The phosphorylation of different sites produces a significant effect on the conformational dynamics ...

Machine learning for predicting cognitive deficits using auditory and demographic factors.

IMPORTANCE: Predicting neurocognitive deficits using complex auditory assessments could change how c...

Precision healthcare: A deep dive into machine learning algorithms and feature selection strategies for accurate heart disease prediction.

This paper presents a comprehensive exploration of machine learning algorithms (MLAs) and feature se...

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which ...

A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data.

To provide accurate predictions, current machine learning-based solutions require large, manually la...

TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in...

Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach.

BACKGROUND: SARS-CoV-2 mRNA vaccines are highly immunogenic in people living with HIV (PLWH) on effe...

An extensive review on lung cancer therapeutics using machine learning techniques: state-of-the-art and perspectives.

There are over 100 types of human cancer, accounting for millions of deaths every year. Lung cancer ...

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis.

BACKGROUND: Early prediction of mortality in individuals with HIV (PWH) has perpetually posed a form...

DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy.

Drug-drug interaction (DDI) may result in clinical toxicity or treatment failure of antiretroviral t...

Optimizing removal of antiretroviral drugs from tertiary wastewater using chlorination and AI-based prediction with response surface methodology.

Chemical and pharmaceutical chemicals found in water sources create substantial risks to human healt...

Artificial intelligence in interventional radiology: state of the art.

Artificial intelligence (AI) has demonstrated great potential in a wide variety of applications in i...

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