AIMC Topic: Adult

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Generative Artificial Intelligence-based Surveillance for Avian Influenza Across a Statewide Healthcare System.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Among all 2024 emergency department visits for acute respiratory illness or conjunctivitis across a statewide healthcare system (n = 13 494), generative artificial intelligence-based surveillance with adjunctive human review rapidly and cost-effectiv...

Association between exposure to air pollution and kidney function decline.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND AND HYPOTHESIS: Chronic kidney disease is a major global health concern, with air pollution increasingly recognized as a key contributor to kidney function decline. This study hypothesizes that exposure to air pollution accelerates kidney ...

Perceptions of artificial intelligence in healthcare: a qualitative study among healthcare professionals in Jordan.

BMJ leader
PURPOSE: While there are studies on this topic, there may be a relative scarcity of research focusing on specific regions, such as Jordan. So, this study aims to gather insights from healthcare providers in Jordan concerning the advantages of integra...

Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance.

The Journal of infectious diseases
BACKGROUND: Invasive mold infections (IMI) can lead to severe morbidity and mortality, but routine public health surveillance is lacking. Although extensive evaluation is needed for clinical diagnosis, case classification prediction models may inform...

Effectiveness of artificial intelligence-based diabetic retinopathy screening in primary care and endocrinology settings in Australia: a pragmatic trial.

The British journal of ophthalmology
PURPOSE: To investigate the diagnostic accuracy, feasibility and end-user experiences of an artificial intelligence (AI)-based, automated diabetic retinopathy (DR) screening model in real-world, Australian primary care and endocrinology clinics.

Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa.

Journal of clinical pathology
BACKGROUND: Deep learning (DL) models are effective pre-screening tools for detecting mismatch repair deficiency (dMMR) in colorectal carcinoma (CRC). These models have been trained and validated on large cohorts from the Northern Hemisphere, without...

Sex-specific body fat distribution predicts cardiovascular ageing.

European heart journal
BACKGROUND AND AIMS: Cardiovascular ageing is a progressive loss of physiological reserve, modified by environmental and genetic risk factors, that contributes to multi-morbidity due to accumulated damage across diverse cell types, tissues, and organ...

Diagnosis of uterine diseases by label-free serum SERS fingerprints with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Early detection of uterine diseases is critically important for women's reproductive health. Here, we propose a novel and robust serum-based SERS analysis platform that integrates machine learning algorithms. This is the first application of it in th...

Combined magnetic resonance imaging and serum analysis reveals distinct multiple sclerosis types.

Brain : a journal of neurology
Multiple sclerosis (MS) is a highly heterogeneous disease in its clinical manifestation and progression. Predicting individual disease courses is key for aligning treatments with underlying pathobiology. We developed an unsupervised machine learning ...