AIMC Topic: Humans

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Knowledge Graph Embeddings for ICU readmission prediction.

BMC medical informatics and decision making
BACKGROUND: Intensive Care Unit (ICU) readmissions represent both a health risk for patients,with increased mortality rates and overall health deterioration, and a financial burden for healthcare facilities. As healthcare became more data-driven with...

A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach.

Scientific reports
Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored with visual field (VF) testing. Deep learning models (DLM) may help identify VF worsening consistently and reproducibly. In this study, we developed and ...

Intra-person multi-task learning method for chronic-disease prediction.

Scientific reports
In the medical field, various clinical information has been accumulated to help clinicians provide personalized medicine and make better diagnoses. As chronic diseases share similar characteristics, it is possible to predict multiple chronic diseases...

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.

Journal of medical Internet research
BACKGROUND: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence (AI) into wearable devices (wearable AI) has been exploited to provid...

Extracting a Novel Emotional EEG Topographic Map Based on a Stacked Autoencoder Network.

Journal of healthcare engineering
Emotion recognition based on brain signals has increasingly become attractive to evaluate human's internal emotional states. Conventional emotion recognition studies focus on developing machine learning and classifiers. However, most of these methods...

Precise Discrimination for Multiple Etiologies of Dementia Cases Based on Deep Learning with Electroencephalography.

Neuropsychobiology
INTRODUCTION: It is critical to develop accurate and universally available biomarkers for dementia diseases to appropriately deal with the dementia problems under world-wide rapid increasing of patients with dementia. In this sense, electroencephalog...

Deep Learning-Based Segmentation of Airway Morphology from Endobronchial Optical Coherence Tomography.

Respiration; international review of thoracic diseases
BACKGROUND: Manual measurement of endobronchial optical coherence tomography (EB-OCT) images means a heavy workload in the clinical practice, which can also introduce bias if the subjective opinions of doctors are involved.

Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals.

PLoS computational biology
Humans can learn several tasks in succession with minimal mutual interference but perform more poorly when trained on multiple tasks at once. The opposite is true for standard deep neural networks. Here, we propose novel computational constraints for...

Machine Learning and Health Care: Potential Benefits and Issues.

The Journal of ambulatory care management
We discuss the potential for machine learning (ML) and artificial intelligence (AI) to improve health care, while detailing caveats and important considerations to ensure unbiased and equitable implementation. If disparities exist in the data used to...

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI).