AIMC Topic: Humans

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Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Experimental biology and medicine (Maywood, N.J.)
Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogene...

The effect of cardiac rhythm on artificial intelligence-enabled ECG evaluation of left ventricular ejection fraction prediction in cardiac intensive care unit patients.

International journal of cardiology
The presence of left ventricular systolic dysfunction (LVSD) alters clinical management and prognosis in most acute and chronic cardiovascular conditions. While transthoracic echocardiography (TTE) remains the most common diagnostic tool to screen fo...

Bayesian convolutional neural network estimation for pediatric pneumonia detection and diagnosis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Pneumonia is a disease that affects the lungs, making breathing difficult. Nowadays, pneumonia is the disease that kills the most children under the age of five in the world, and if no action is taken, pneumonia is estimate...

The cardiovascular phenotype of Chronic Obstructive Pulmonary Disease (COPD): Applying machine learning to the prediction of cardiovascular comorbidities.

Respiratory medicine
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous group of lung conditions that are challenging to diagnose and treat. As the presence of comorbidities often exacerbates this scenario, the characterization of patients with C...

ncRDense: A novel computational approach for classification of non-coding RNA family by deep learning.

Genomics
With the rapidly growing importance of biological research, non-coding RNAs (ncRNA) attract more attention in biology and bioinformatics. They play vital roles in biological processes such as transcription and translation. Classification of ncRNAs is...

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.

Circulation
BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to deve...

Prediction Model Using Machine Learning for Mortality in Patients with Heart Failure.

The American journal of cardiology
Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US population, the public health burden of HF is enormous. We aimed to develop an ensemble prediction model for 30-day mortality after discharge using machine...

Comparison of machine learning techniques for the identification of human activities from inertial sensors available in a mobile device after the application of data imputation techniques.

Computers in biology and medicine
Human activity recognition (HAR) is a significant research area due to its wide range of applications in intelligent health systems, security, and entertainment games. Over the past few years, many studies have recognized human daily living activitie...

A sensitivity analysis of probability maps in deep-learning-based anatomical segmentation.

Journal of applied clinical medical physics
PURPOSE: Deep-learning-based segmentation models implicitly learn to predict the presence of a structure based on its overall prominence in the training dataset. This phenomenon is observed and accounted for in deep-learning applications such as natu...

DCANet: Dual contextual affinity network for mass segmentation in whole mammograms.

Medical physics
PURPOSE: Breast mass segmentation in mammograms remains a crucial yet challenging topic in computer-aided diagnosis systems. Existing algorithms mainly used mass-centered patches to achieve mass segmentation, which is time-consuming and unstable in c...