AIMC Topic: Humans

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Analysis of Potential for User Errors in Mobile Deployment of Radiology Deep Learning for Cardiac Rhythm Device Detection.

Journal of digital imaging
We examine how convolutional neural networks (CNNs) for cardiac rhythm device detection can exhibit failures in performance under suboptimal deployment scenarios and examine how medically adversarial image presentation can further impair neural netwo...

Brain age prediction: A comparison between machine learning models using region- and voxel-based morphometric data.

Human brain mapping
Brain morphology varies across the ageing trajectory and the prediction of a person's age using brain features can aid the detection of abnormalities in the ageing process. Existing studies on such "brain age prediction" vary widely in terms of their...

Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases.

Computers in biology and medicine
Corona Virus Disease (COVID-19) has been announced as a pandemic and is spreading rapidly throughout the world. Early detection of COVID-19 may protect many infected people. Unfortunately, COVID-19 can be mistakenly diagnosed as pneumonia or lung can...

Automatic phenotyping of electronical health record: PheVis algorithm.

Journal of biomedical informatics
Electronic Health Records (EHRs) often lack reliable annotation of patient medical conditions. Phenorm, an automated unsupervised algorithm to identify patient medical conditions from EHR data, has been developed. PheVis extends PheNorm at the visit ...

AI-based smartphone apps for risk assessment of skin cancer need more evaluation and better regulation.

British journal of cancer
Smartphone applications ("apps") with artificial intelligence (AI) algorithms are increasingly used in healthcare. Widespread adoption of these apps must be supported by a robust evidence-base and app manufacturers' claims appropriately regulated. Cu...

Image processing and machine learning for telehealth craniosynostosis screening in newborns.

Journal of neurosurgery. Pediatrics
OBJECTIVE: The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was ...

Image-based deep learning in diagnosing the etiology of pneumonia on pediatric chest X-rays.

Pediatric pulmonology
PURPOSE: Comparing the efficacy of a deep-learning model in classifying the etiology of pneumonia on pediatric chest X-rays (CXRs) with that of human readers.

Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism.

Sensors (Basel, Switzerland)
Arterial blood pressure (ABP) is an important vital sign from which it can be extracted valuable information about the subject's health. After studying its morphology it is possible to diagnose cardiovascular diseases such as hypertension, so ABP rou...

DRER: Deep Learning-Based Driver's Real Emotion Recognizer.

Sensors (Basel, Switzerland)
In intelligent vehicles, it is essential to monitor the driver's condition; however, recognizing the driver's emotional state is one of the most challenging and important tasks. Most previous studies focused on facial expression recognition to monito...

Design of a Sensitive Balloon Sensor for Safe Human-Robot Interaction.

Sensors (Basel, Switzerland)
As the safety of a human body is the main priority while interacting with robots, the field of tactile sensors has expanded for acquiring tactile information and ensuring safe human-robot interaction (HRI). Existing lightweight and thin tactile senso...