AIMC Topic: Disease Progression

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Emerging use of pulmonary artery and cardiac pressure sensing technology in the management of worsening heart failure events.

Heart failure reviews
Unplanned admissions for worsening heart failure (WHF) are the largest resource cost in heart failure (HF) management. Despite advances in pharmacological agents and interventional therapy, HF remains a global epidemic. One crucial-and costly-gap in ...

Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3-5: A Multicenter Study Using the Machine Learning Approach.

Studies in health technology and informatics
Chronic Kidney Disease (CKD) is a prevalent and progressive condition that can lead to end-stage renal disease (ESRD) if left unmanaged. Accurate prediction of CKD progression, particularly in patients with CKD stages 3-5, is essential for early inte...

Time-Aware Tranformer-Based Prediction Model for AECOPD.

Studies in health technology and informatics
The rapid symptom change of Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) makes it critical to have time-sensitive prediction models. However, most current machine learning models studying AECOPD use clinical and laboratory dat...

Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.

Pharmacoepidemiology and drug safety
BACKGROUND: Glucagon-like Peptide-1 Receptor Agonists (GLP1RA) may reduce asthma exacerbation (AE) risk, but it is unclear which populations benefit most. Recent pharmacoepidemiologic studies have employed iterative causal forest (iCF), a machine lea...

Emerging Technologies and Algorithms for Periodontal Screening and Risk of Disease Progression in Non-Dental Settings: A Scoping Review.

Journal of clinical periodontology
AIM: To evaluate different tools to screen for periodontal diseases and/or evaluate the risk for disease progression in non-dental clinical settings.

From resting-state functional hippocampal centrality to functional outcome: An extended neurocognitive model of psychosis.

Psychiatry research
BACKGROUND: We previously proposed a neurocognitive model of psychosis in which reduced morphometric hippocampal-cortical connectivity precedes impaired episodic memory, social cognition, negative symptoms, and functional outcome. We provided support...

Clinical relevance of computationally derived tubular features and their spatial relationships with the interstitial microenvironment in minimal change disease/focal segmental glomerulosclerosis.

Kidney international
BACKGROUND: Visual scoring of tubular damage has limitations in capturing the full spectrum of structural changes and prognostic potential. Here, we investigated if computationally quantified tubular features can enhance prognostication and reveal sp...

Brain age prediction from MRI scans in neurodegenerative diseases.

Current opinion in neurology
PURPOSE OF REVIEW: This review explores the use of brain age estimation from MRI scans as a biomarker of brain health. With disorders like Alzheimer's and Parkinson's increasing globally, there is an urgent need for early detection tools that can ide...

Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach.

Artificial intelligence in medicine
Chronic kidney disease (CKD) poses a significant risk for diabetes patients, often leading to severe complications. Early and accurate CKD stage detection is crucial for timely intervention. However, it remains challenging due to its asymptomatic pro...

Exploring oculomotor challenges in amyotrophic lateral sclerosis: a comprehensive review.

Amyotrophic lateral sclerosis & frontotemporal degeneration
Traditionally understood as a motor neuron disease, amyotrophic lateral sclerosis (ALS) is now recognized to involve broader neurodegenerative processes, including the oculomotor system. This narrative review summarizes current evidence on oculomotor...