AIMC Topic: Humans

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Cascaded Deep Learning Neural Network for Automated Liver Steatosis Diagnosis Using Ultrasound Images.

Sensors (Basel, Switzerland)
Diagnosing liver steatosis is an essential precaution for detecting hepatocirrhosis and liver cancer in the early stages. However, automatic diagnosis of liver steatosis from ultrasound (US) images remains challenging due to poor visual quality from ...

Object Manipulation with an Anthropomorphic Robotic Hand via Deep Reinforcement Learning with a Synergy Space of Natural Hand Poses.

Sensors (Basel, Switzerland)
Anthropomorphic robotic hands are designed to attain dexterous movements and flexibility much like human hands. Achieving human-like object manipulation remains a challenge especially due to the control complexity of the anthropomorphic robotic hand ...

Automated Bowel Sound Analysis: An Overview.

Sensors (Basel, Switzerland)
Despite technological progress, we lack a consensus on the method of conducting automated bowel sound (BS) analysis and, consequently, BS tools have not become available to doctors. We aimed to briefly review the literature on BS recording and analys...

Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model.

Sensors (Basel, Switzerland)
Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person suffering from diabetes. Diabetic macular edema (DME) occurs when DR affects the macula, which causes fluid accumulation in the macula. Efficient screening systems ...

Falcon: A False Ceiling Inspection Robot.

Sensors (Basel, Switzerland)
Frequent inspections are essential for false ceilings to maintain the service infrastructures, such as mechanical, electrical, and plumbing, and the structure of false ceilings. Human-labor-based conventional inspection procedures for false ceilings ...

Deep learning of contagion dynamics on complex networks.

Nature communications
Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematically or computationally tractable, these models must rely on simplifying assumptions, thereby limiti...

Detection of subclinical rheumatic heart disease in children using a deep learning algorithm on digital stethoscope: a study protocol.

BMJ open
INTRODUCTION: Rheumatic heart diseases (RHDs) contribute significant morbidity and mortality globally. To reduce the burden of RHD, timely initiation of secondary prophylaxis is important. The objectives of this study are to determine the frequency o...

ACCV: automatic classification algorithm of cataract video based on deep learning.

Biomedical engineering online
PURPOSE: A real-time automatic cataract-grading algorithm based on cataract video is proposed.

Computer-aided diagnosis with a convolutional neural network algorithm for automated detection of urinary tract stones on plain X-ray.

BMC urology
BACKGROUND: Recent increased use of medical images induces further burden of their interpretation for physicians. A plain X-ray is a low-cost examination that has low-dose radiation exposure and high availability, although diagnosing urolithiasis usi...

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

eLife
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrai...