AIMC Topic: Female

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Early sepsis mortality prediction model based on interpretable machine learning approach: development and validation study.

Internal and emergency medicine
Sepsis triggers a harmful immune response due to infection, causing high mortality. Predicting sepsis outcomes early is vital. Despite machine learning's (ML) use in medical research, local validation within the Medical Information Mart for Intensive...

Differentiating hand gestures from forearm muscle activity using machine learning.

International journal of occupational safety and ergonomics : JOSE
This study explored the use of forearm electromyography data to distinguish eight hand gestures. The neural network (NN) and random forest (RF) algorithms were tested on data from 10 participants. As window sizes increase from 200 ms to 1000 ms, the ...

Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.

JACC. Cardiovascular imaging
BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to severe AS or by the effects of comorbidities. In the absence of randomized trial evidence favoring aortic valve replacement (AVR) in patients with moderat...

An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.

JACC. Cardiovascular imaging
BACKGROUND: Considering the high prevalence of mitral regurgitation (MR) and the highly subjective, variable MR severity reporting, an automated tool that could screen patients for clinically significant MR (≥ moderate) would streamline the diagnosti...

Deep learning segmentation of mandible with lower dentition from cone beam CT.

Oral radiology
OBJECTIVES: This study aimed to train a 3D U-Net convolutional neural network (CNN) for mandible and lower dentition segmentation from cone-beam computed tomography (CBCT) scans.

Can Patients With Urogenital Cancer Rely on Artificial Intelligence Chatbots for Treatment Decisions?

Clinical genitourinary cancer
OBJECTIVES: In the era of artificial intelligence, almost half of the patients use the internet to get information about their diseases. Our study aims to demonstrate the reliability of the information provided by artificial intelligence chatbots (AI...

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task.

Journal of affective disorders
One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS...

Deep learning and its associated factors among Chinese nursing undergraduates: A cross-sectional study.

Nurse education today
BACKGROUND: Adequate professional preparation of nursing undergraduates is conducive to developing health care careers. Deep learning is important for enhancing nursing competencies and the overall quality of students. However, limited research has b...

Artificial intelligence tools utilized in nursing education: Incidence and associated factors.

Nurse education today
BACKGROUND: Artificial intelligence technology is among the most significant advancements that provide students with effective learning opportunities in this digital era. Therefore, the National League for Nursing states that it is necessary to refra...