AIMC Topic: Humans

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An Interpretable Deep Learning Model for Speech Activity Detection Using Electrocorticographic Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Numerous state-of-the-art solutions for neural speech decoding and synthesis incorporate deep learning into the processing pipeline. These models are typically opaque and can require significant computational resources for training and execution. A d...

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images.

IEEE/ACM transactions on computational biology and bioinformatics
Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great importance and urgency during the worldwide outbreak. However, radiologists have to distinguish COVID-19 pneumonia from other pneumonia in a large num...

Estimating tree-based dynamic treatment regimes using observational data with restricted treatment sequences.

Biometrics
A dynamic treatment regime (DTR) is a sequence of decision rules that provide guidance on how to treat individuals based on their static and time-varying status. Existing observational data are often used to generate hypotheses about effective DTRs. ...

Machine learning-based prediction of disability risk in geriatric patients with hypertension for different time intervals.

Archives of gerontology and geriatrics
BACKGROUND: The risk of disability in older adults with hypertension is substantially high, and prediction of disability risk is crucial for subsequent management. This study aimed to construct prediction models of disability risk for geriatric patie...

Artificial Intelligence and Big Data Science in Neurocritical Care.

Critical care clinics
In recent years, the volume of digitalized web-based information utilizing modern computer-based technology for data storage, processing, and analysis has grown rapidly. Humans can process a limited number of variables at any given time. Thus, the de...

Efficacy and Safety of Robot-assisted AUS Implantation Surgery in Treating Severe Stress Urinary Incontinence: A Systematic Review and Meta-Analysis.

Urology
OBJECTIVE: To investigate the effectiveness and safety of robot-assisted artificial urinary sphincter (AUS) implantation surgery for female patients with severe stress urinary incontinences (SUI) by performing a systematic literature review.

Image quality improvement in low-dose chest CT with deep learning image reconstruction.

Journal of applied clinical medical physics
OBJECTIVES: To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low-dose chest CT in comparison with 40% adaptive statistical iterative reconstruction-Veo (ASiR-V40%) algorithm.

A manifesto on explainability for artificial intelligence in medicine.

Artificial intelligence in medicine
The rapid increase of interest in, and use of, artificial intelligence (AI) in computer applications has raised a parallel concern about its ability (or lack thereof) to provide understandable, or explainable, output to users. This concern is especia...

Artificial Intelligence in Oral and Maxillofacial Surgery Education.

Oral and maxillofacial surgery clinics of North America
Artificial intelligence has become ubiquitous with modern technology. Digital transformations are occurring in every field including medicine, surgery, and education. Computers and computer programs are getting sophisticated to form neural networks g...

Study on the Classification of Metal Objects by a Fluxgate Magnetometer Cube Structure.

Sensors (Basel, Switzerland)
After wars, some unexploded bombs remained underground, and these faulty bombs seriously threaten the safety of people. The ability to accurately identify targets is crucial for subsequent mining work. A deep learning algorithm is used to recognize t...