AIMC Topic: Humans

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Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This study demonstrates deep learning approaches with an aim to find the optimal method to automatically detect sleep apnea (SA) events from an electrocardiogram (ECG) signal.

Predicting death by suicide using administrative health care system data: Can feedforward neural network models improve upon logistic regression models?

Journal of affective disorders
BACKGROUND: Suicide is a leading cause of death worldwide. With the increasing volume of administrative health care data, there is an opportunity to evaluate whether machine learning models can improve upon statistical models for quantifying suicide ...

Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease).

Journal of biomedical informatics
AIM: The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical softwa...

Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Manual feedback from senior surgeons observing less experienced trainees is a laborious task that is very expensive, time-consuming and prone to subjectivity. With the number of surgical procedures increasing annually, there is an unpreceden...

Retinal image assessment using bi-level adaptive morphological component analysis.

Artificial intelligence in medicine
The automated analysis of retinal images is a widely researched area which can help to diagnose several diseases like diabetic retinopathy in early stages of the disease. More specifically, separation of vessels and lesions is very critical as featur...

Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach.

Sensors (Basel, Switzerland)
Bushfires are becoming more frequent and intensive due to changing climate. Those that occur close to vineyards can cause smoke contamination of grapevines and grapes, which can affect wines, producing smoke-taint. At present, there are no available ...

Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BMC biology
BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is a major challenge of modern genomics, especially for precision medicine. Transcription factor (TF) binding profiles and epigenomic landscapes in refe...

Using distant supervision to augment manually annotated data for relation extraction.

PloS one
Significant progress has been made in applying deep learning on natural language processing tasks recently. However, deep learning models typically require a large amount of annotated training data while often only small labeled datasets are availabl...

A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning.

IEEE journal of biomedical and health informatics
The ballistocardiography (BCG) signal is a measurement of the vibrations of the center of mass of the body due to the cardiac cycle and can be used for noninvasive hemodynamic monitoring. The seismocardiography (SCG) signals measure the local vibrati...