AIMC Topic: Deep Learning

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Exploring the Intersection between Social Determinants of Health and Unmet Dental Care Needs Using Deep Learning.

International journal of environmental research and public health
The goals of this study were to develop a risk prediction model in unmet dental care needs and to explore the intersection between social determinants of health and unmet dental care needs in the United States. Data from the 2016 Medical Expenditure ...

Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography.

Scandinavian journal of trauma, resuscitation and emergency medicine
BACKGROUND: In-hospital cardiac arrest is a major burden in health care. Although several track-and-trigger systems are used to predict cardiac arrest, they often have unsatisfactory performances. We hypothesized that a deep-learning-based artificial...

Efficient molecular encoders for virtual screening.

Drug discovery today. Technologies
Molecular representations encoding molecular structure information play critical roles in molecular virtual screening (VS). In order to improve VS performance, an abundance of molecular encoders have been developed and tested by various VS challenges...

Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.

International journal of computer assisted radiology and surgery
PURPOSE: The main purpose of this study is to construct a system to track the tumor position during radiofrequency ablation (RFA) treatment. Existing tumor tracking systems are designed to track a tumor in a two-dimensional (2D) ultrasound (US) image...

Detecting myocardial scar using electrocardiogram data and deep neural networks.

Biological chemistry
Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischae...

Non-invasive setup for grape maturation classification using deep learning.

Journal of the science of food and agriculture
BACKGROUND: The San Francisco Valley region from Brazil is known worldwide for its fruit production and exportation, especially grapes and wines. The grapes have high quality not only due to the excellent morphological characteristics, but also to th...

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms.

Scientific reports
Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging...

Quantifying the usage of small public spaces using deep convolutional neural network.

PloS one
Small public spaces are the key built environment elements that provide venues for various of activities. However, existing measurements or approaches could not efficiently and effectively quantify how small public spaces are being used. In this pape...

Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning.

Molecular psychiatry
Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurob...

A deep learning-based, unsupervised method to impute missing values in electronic health records for improved patient management.

Journal of biomedical informatics
Electronic health records (EHRs) often suffer missing values, for which recent advances in deep learning offer a promising remedy. We develop a deep learning-based, unsupervised method to impute missing values in patient records, then examine its imp...