AIMC Topic: Machine Learning

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Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing.

Scientific reports
The relationship between ischemic stroke (IS) and pyroptosis centers on the inflammatory response elicited by cerebral tissue damage during an ischemic stroke event. However, an in-depth mechanistic understanding of their connection remains limited. ...

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

Scientific reports
The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging as a reported concern in vaccinated females. We aimed to develop a machine learning (ML) model to pre...

Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency department.

Scientific reports
Radiocontrast media is a major cause of nephrotoxic acute kidney injury(AKI). Contrast-enhanced CT(CE-CT) is commonly performed in emergency departments(ED). Predicting individualized risks of contrast-associated AKI(CA-AKI) in ED patients is challen...

Using machine learning to predict deterioration of symptoms in COPD patients within a telemonitoring program.

Scientific reports
COPD exacerbations have a profound clinical impact on patients. Accurately predicting these events could help healthcare professionals take proactive measures to mitigate their impact. For over a decade, telEPOC, a telehealthcare program, has collect...

Feature-Based Audiogram Value Estimator (FAVE): Estimating Numerical Thresholds from Scanned Images of Handwritten Audiograms.

Journal of medical systems
Hearing loss is a public health concern that affects millions of people globally. Clinically, a person's hearing sensitivity is often measured using pure-tone audiometry and visualized as a pure-tone audiogram, a plot of hearing sensitivity as a func...

Advancing regenerative medicine: the Aceman system's pioneering automation and machine learning in mesenchymal stem cell biofabrication.

Biofabrication
Mesenchymal stem cells (MSCs) are pivotal in advancing regenerative medicine; however, the large-scale production of MSCs for clinical applications faces significant challenges related to efficiency, cost, and quality assurance. We introduce the Auto...

Machine Learning-Based Mortality Prediction for Acute Gastrointestinal Bleeding Patients Admitted to Intensive Care Unit.

Current medical science
OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patients with acute gastrointestinal bleeding (AGIB) in the intensive care unit (ICU) and compared their prognostic performance with that of Acute Physiolo...

Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer.

Frontiers in endocrinology
OBJECTIVE: This study explores the value of combining intratumoral and peritumoral radiomics features from ultrasound imaging with clinical characteristics to assess axillary lymph node burden in breast cancer patients.

Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study.

Frontiers in immunology
INTRODUCTION: Knee osteoarthritis (KOA) is a degenerative joint disease characterized by the progressive deterioration of cartilage and synovial inflammation. A critical mechanism in the pathogenesis of KOA is impaired efferocytosis in synovial tissu...

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...