AIMC Topic: Humans

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Comparing different deep learning architectures for classification of chest radiographs.

Scientific reports
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research. However, most of the models used to classify chest radiographs are derived from openly available deep neural networks,...

Rapid identification of COVID-19 severity in CT scans through classification of deep features.

Biomedical engineering online
BACKGROUND: Chest CT is used for the assessment of the severity of patients infected with novel coronavirus 2019 (COVID-19). We collected chest CT scans of 202 patients diagnosed with the COVID-19, and try to develop a rapid, accurate and automatic t...

Role of Assistive Robots in the Care of Older People: Survey Study Among Medical and Nursing Students.

Journal of medical Internet research
BACKGROUND: Populations are aging at an alarming rate in many countries around the world. There has been not only a decrease in the number of births and an increase in the percentage of older people, but also an increase in the number of people livin...

Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tw...

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism.

Journal of medical Internet research
BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suit...

Engineering recurrent neural networks from task-relevant manifolds and dynamics.

PLoS computational biology
Many cognitive processes involve transformations of distributed representations in neural populations, creating a need for population-level models. Recurrent neural network models fulfill this need, but there are many open questions about how their c...

Identifying controllable cortical neural markers with machine learning for adaptive deep brain stimulation in Parkinson's disease.

NeuroImage. Clinical
The identification of oscillatory neural markers of Parkinson's disease (PD) can contribute not only to the understanding of functional mechanisms of the disorder, but may also serve in adaptive deep brain stimulation (DBS) systems. These systems see...

Expectations versus reality: trainee participation on the robotic console in academic surgery.

Surgical endoscopy
INTRODUCTION: Trainees underestimate the amount of operative autonomy they receive, whereas faculty overestimate; this has not been studied in robotics. We aimed to assess the perceptions and expectations of our general surgery trainees and faculty o...

Artificial intelligence powered statistical genetics in biobanks.

Journal of human genetics
Large-scale, sometimes nationwide, prospective genomic cohorts biobanking rich biological specimens such as blood, urine and tissues, have been established and released their vast amount of data in several countries. These genetic and epidemiological...

Design and control of a lower limb rehabilitation robot considering undesirable torques of the patient's limb.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This research introduces a new exoskeleton-type rehabilitation robot, which can be used in lower limb rehabilitation therapy for post-stroke patients. A novel design of a typical knee and ankle rehabilitation robot is proposed. The kinematic and dyna...