Latest AI and machine learning research in infection control / modes of transmission for healthcare professionals.
BACKGROUND: The heterogeneity of COVID-19 spread dynamics is determined by complex spatiotemporal transmission patterns at a fine scale, especially in densely populated regions. In this study, we aim to discover such fine-scale transmission patterns via deep learning.
Pollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning models with a focus on deep learning, have an essential role in the pollen classification task. Within this study we developed an explainable framework to unveil a deep learning model for pollen classification. Model works on data coming from single ...
This paper investigates a class of power consumption minimization and equalization for intelligent and connected vehicles cooperative system. Accordin...
We present the first implementation of the monitoring of airborne fungal spores in real-time using digital holography. To obtain observations of spp....
In recent years, thanks to advances in computer hardware and dataset availability, data-driven approaches (like machine learning) have become one of t...
Archaea are a vast and unexplored cellular domain that thrive in a high diversity of environments, having central roles in processes mediating global ...
Breathing monitoring is an efficient way of human health sensing and predicting numerous diseases. Various contact and non-contact-based methods are d...
Nanophotonics exploits the best of photonics and nanotechnology which has transformed optics in recent years by allowing subwavelength structures to e...
Inchworm-inspired bionic soft crawling robot (SCR) composed of soft materials possesses preeminent active compliant deformation ability and has obviou...
Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinica...
Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM syste...
In this work, a large-scale tactile detection system is proposed, whose development is based on a soft structure using Machine Learning and Computer V...
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the ...
Vision is the main component of current robotics systems that is used for manipulating objects. However, solely relying on vision for hand-object pose...
Miniature magnetic soft machines could significantly impact minimally invasive robotics and biomedical applications. However, most soft machines are l...
Phased array-based full-matrix ultrasonic imaging has been the golden standard for the non-destructive evaluation of critical components. However, the...
Regardless of recent advances, humanoid robots still face significant difficulties in performing locomotion tasks. Among the key challenges that must ...
1-Hydroxypyrene (1-OHPyr), a typical hydroxylated polycyclic aromatic hydrocarbon (OH-PAH), has been commonly regarded as a urinary biomarker for asse...
Malaria, caused by Plasmodium parasites, is a major global health challenge. Whole genome sequencing (WGS) of Plasmodium falciparum and Plasmodium viv...
On-site nucleic acid testing (NAT) plays an important role for disease monitoring and pathogen diagnosis. In this work, we developed an automated and ...