AIMC Topic: Humans

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Artificial neural network based prediction of postthrombolysis intracerebral hemorrhage and death.

Scientific reports
Despite the salient benefits of the intravenous tissue plasminogen activator (tPA), symptomatic intracerebral hemorrhage (sICH) remains a frequent complication and constitutes a major concern when treating acute ischemic stroke (AIS). This study expl...

Machine-learning classification of texture features of portable chest X-ray accurately classifies COVID-19 lung infection.

Biomedical engineering online
BACKGROUND: The large volume and suboptimal image quality of portable chest X-rays (CXRs) as a result of the COVID-19 pandemic could post significant challenges for radiologists and frontline physicians. Deep-learning artificial intelligent (AI) meth...

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: It is important to measure the public response to the COVID-19 pandemic. Twitter is an important data source for infodemiology studies involving public response monitoring.

A Method to Improve Availability and Quality of Patient Race Data in an Electronic Health Record System.

Applied clinical informatics
BACKGROUND: Although federal regulations mandate documentation of structured race data according to Office of Management and Budget (OMB) categories in electronic health record (EHR) systems, many institutions have reported gaps in EHR race data that...

Artificial intelligence to predict the BRAFV600E mutation in patients with thyroid cancer.

PloS one
PURPOSE: To investigate whether a computer-aided diagnosis (CAD) program developed using the deep learning convolutional neural network (CNN) on neck US images can predict the BRAFV600E mutation in thyroid cancer.

Identifying transcriptomic correlates of histology using deep learning.

PloS one
Linking phenotypes to specific gene expression profiles is an extremely important problem in biology, which has been approached mainly by correlation methods or, more fundamentally, by studying the effects of gene perturbations. However, genome-wide ...

SE-stacking: Improving user purchase behavior prediction by information fusion and ensemble learning.

PloS one
Online shopping behavior has the characteristics of rich granularity dimension and data sparsity and presents a challenging task in e-commerce. Previous studies on user behavior prediction did not seriously discuss feature selection and ensemble desi...

Challenges in the Development, Deployment, and Regulation of Artificial Intelligence in Anatomic Pathology.

The American journal of pathology
Significant advances in artificial intelligence (AI), deep learning, and other machine-learning approaches have been made in recent years, with applications found in almost every industry, including health care. AI is capable of completing a spectrum...

Robust water-fat separation based on deep learning model exploring multi-echo nature of mGRE.

Magnetic resonance in medicine
PURPOSE: To design a new deep learning network for fast and accurate water-fat separation by exploring the correlations between multiple echoes in multi-echo gradient-recalled echo (mGRE) sequence and evaluate the generalization capabilities of the n...

Update on benign paroxysmal positional vertigo.

Journal of neurology
Benign paroxysmal positional vertigo (BPPV) is the most common cause of vertigo worldwide. This review considers recent advances in the diagnosis and management of BPPV including the use of web-based technology and artificial intelligence as well as ...