AIMC Topic: Aged

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Predicting prolonged length of in-hospital stay in patients with non-ST elevation myocardial infarction (NSTEMI) using artificial intelligence.

International journal of cardiology
BACKGROUND: Patients presenting with non-ST elevation myocardial infarction (NSTEMI) are typically evaluated using coronary angiography and managed through coronary revascularization. Numerous studies have demonstrated the benefits of expedited disch...

Predicting rheumatoid arthritis in the middle-aged and older population using patient-reported outcomes: insights from the SHARE cohort.

International journal of medical informatics
BACKGROUND: In light of global population aging and the increasing prevalence of Rheumatoid Arthritis (RA) with age, strategies are needed to address this public health challenge. Machine learning (ML) may play a vital role in early identification of...

An Advanced Self-Similarity Measure: Average of Level-Pairwise Hurst Exponent Estimates (ALPHEE).

IEEE transactions on bio-medical engineering
Many natural processes are characterized by complex patterns of self-similarity, where repetitive structures occur across different resolutions. The Hurst exponent is a key parameter used to quantify this self-similarity. While wavelet-based techniqu...

Phenotypic clustering analysis of patients rejected for mitral valve interventions: implications for future transcatheter technologies.

European heart journal. Cardiovascular Imaging
AIMS: Although several treatment options are available for patients with severe mitral regurgitation (MR), a significant proportion of patients remain ineligible for any mitral valve (MV) intervention. We aimed to analyse the phenotypic characteristi...

Patient prioritization for pharmaceutical intervention in the hospital setting: a retrospective cross-sectional study.

The International journal of pharmacy practice
OBJECTIVES: Prioritization of patients requiring pharmaceutical intervention is critical given limited resources. Data from pharmacy software could be used to target patients. This retrospective cross-sectional study aimed to describe the method impl...

An FDG-PET-Based Machine Learning Framework to Support Neurologic Decision-Making in Alzheimer Disease and Related Disorders.

Neurology
BACKGROUND AND OBJECTIVES: Distinguishing neurodegenerative diseases is a challenging task requiring neurologic expertise. Clinical decision support systems (CDSSs) powered by machine learning (ML) and artificial intelligence can assist with complex ...

Role of Brain Age Gap as a Mediator in the Relationship Between Cognitive Impairment Risk Factors and Cognition.

Neurology
BACKGROUND AND OBJECTIVES: Cerebrovascular disease (CeVD) and cognitive impairment risk factors contribute to cognitive decline, but the role of brain age gap (BAG) in mediating this relationship remains unclear, especially in Southeast Asian populat...

Application of Fourier transform infrared (FTIR) spectroscopy in liquid biopsy to predict the response to the first-line immunotherapy in non-small-cell lung cancer (NSCLC) patients.

Biochemical and biophysical research communications
The direction of anticancer therapies has changed in recent years, including the increasing use of immunotherapy. However, around 50 % of non-small-cell lung cancer (NSCLC) patients do not respond to immunotherapy. Therefore, it is important to find ...

Deep learning for echocardiographic assessment and risk stratification of aortic, mitral, and tricuspid regurgitation: the DELINEATE-regurgitation study.

European heart journal
BACKGROUND AND AIMS: Classification and risk stratification in aortic (AR), mitral (MR), and tricuspid regurgitation (TR) remains a significant clinical challenge. This study aimed to develop an artificial intelligence (AI) system to assess valvular ...