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[Incidence and determinants of viral load rebound in people receiving multi-month dispensing of antiretroviral therapy at the Regional Annex Hospital of Dschang from 2018-2023].

The Pan African medical journal
INTRODUCTION: in Cameroon, multi-month dispensing (MMD) of antiretrovirals (ARVs) was introduced to improve treatment adherence among people living with HIV (PLHIV). However, this strategy has limitations that may lead to viral load rebound. The purp...

Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

Clinical interventions in aging
BACKGROUND: Hip fractures have become a significant health concern, particularly among super-aged patients, who were at a high risk of postoperative pneumonia due to their frailty and the presence of multiple comorbidities. This study aims to establi...

Machine learning model-based prediction of postpancreatectomy acute pancreatitis following pancreaticoduodenectomy: A retrospective cohort study.

World journal of gastroenterology
BACKGROUND: The International Study Group of Pancreatic Surgery has established the definition and grading system for postpancreatectomy acute pancreatitis (PPAP). There are no established machine learning models for predicting PPAP following pancrea...

Study on the prediction performance of AIDS monthly incidence in Xinjiang based on time series and deep learning models.

BMC public health
OBJECTIVE: AIDS is a highly fatal infectious disease of Class B, and Xinjiang is a high-incidence region for AIDS in China. The core of prevention and control lies in early monitoring and early warning. This study aims to identify the best model for ...

Predicting major adverse cardiac events in diabetes and chronic kidney disease: a machine learning study from the Silesia Diabetes-Heart Project.

Cardiovascular diabetology
BACKGROUND: People living with diabetes mellitus (DM) and chronic kidney disease (CKD) are at significantly high risk of cardiovascular events (CVEs), however the predictive performance of traditional risk prediction methods are limited.

Perioperative goal-directed therapy with artificial intelligence to reduce the incidence of intraoperative hypotension and renal failure in patients undergoing lung surgery: A pilot study.

Journal of clinical anesthesia
STUDY OBJECTIVE: The aim of this study was to investigate whether goal-directed treatment using artificial intelligence, compared to standard care, can reduce the frequency, duration, and severity of intraoperative hypotension in patients undergoing ...

Risk evaluation and incidence prediction of endolymphatic hydrops using multilayer perceptron in patients with audiovestibular symptoms.

Medicine
Endolymphatic hydrops (EH) has been visualized on magnetic resonance imaging (MRI) in patients with various inner ear diseases. The purpose of this study was to evaluate the prevalence and risk factors of significant EH on inner ear MRI in patients w...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive decline remains under-explored.

Artificial intelligence-driven 3D MRI of lumbosacral nerve root anomalies: accuracy, incidence, and clinical utility.

Neuroradiology
PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoperative nerve injury. However, it is often difficult to evaluate them with preoperative imaging. We developed a software that automatically generates th...