AIMC Topic: Aged

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Association between the COVID-19 pandemic and cardiopulmonary function in acute coronary syndrome patients without SARS-CoV-2 infection.

Scientific reports
The COVID-19 pandemic disrupted cardiovascular disease management. This single-center cross-sectional cohort study evaluated cardiopulmonary function changes in acute coronary syndrome (ACS) patients post-percutaneous coronary intervention (PCI) with...

Circulating proteins and metabolites panel for noninvasive preoperative diagnosis of epithelial ovarian cancer.

BMC medicine
BACKGROUND: Existing biomarkers for epithelial ovarian cancer (EOC) have demonstrated limited sensitivity and specificity. This study aimed to investigate plasma protein and metabolite characteristics of EOC and identify novel biomarker candidates fo...

Study on the mechanisms associating community outdoor public spaces with elderly behavior.

Scientific reports
As the global population ages, enhancing community outdoor public spaces to accommodate the needs of senior citizens has emerged as a critical challenge. This research delves into the intricate relationship between community outdoor public spaces and...

Radiomics early assessment of post chemotherapy cardiotoxicity in cancer patients using 2D echocardiography imaging an interpretable machine learning study.

Scientific reports
Cardiotoxicity is the loss of the heart muscle's ability to contract effectively, often due to chemotherapy or radiation therapy. This study uses interpretable machine learning to predict post-chemotherapy cardiotoxicity using radiomics features extr...

Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records.

Scientific reports
Heart failure (HF) is a condition with periods of stability interrupted by periods of worsening symptoms, known as decompensation episodes. Digital interventions are promising tools to alleviate burdens on HF management through automated alerts at th...

Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases.

Open heart
BACKGROUND: There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior cardiovascular diseases (CVDs) to facilitate early intervention. This study aimed to develop and validate an AF prediction model using ma...

Deep Learning-Based Early Warning Systems in Hospitalized Patients at Risk of Code Blue Events and Length of Stay: Retrospective Real-World Implementation Study.

JMIR medical informatics
BACKGROUND: In hospitals, Code Blue is an emergency that refers to a patient requiring immediate resuscitation. Over 85% of patients with cardiopulmonary arrest exhibit abnormal vital sign trends prior to the event. Continuous monitoring and accurate...

AI-Based EMG Reporting: A Randomized Controlled Trial.

Journal of neurology
BACKGROUND AND OBJECTIVES: Accurate interpretation of electrodiagnostic (EDX) studies is essential for the diagnosis and management of neuromuscular disorders. Artificial intelligence (AI) based tools may improve consistency and quality of EDX report...

Deep learning model for predicting extraprostatic extension of prostate cancer based on H&E-stained biopsy digital images.

Annals of medicine
BACKGROUND: To develop and validate a deep learning pipeline using prostate biopsy H&E slides to predict extraprostatic extension (EPE) in prostate cancer (PCa) patients.

Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy.

Scientific reports
Prostate cancer remains a significant public health concern, with a substantial proportion of patients experiencing biochemical recurrence (BCR) after radical prostatectomy (RP). Traditional risk models, such as CAPRA-S, have demonstrated moderate pr...