AIMC Topic: Particle Size
Clear Filters Showing 51 to 60 of 195 articles
Magnetic Microrobot Swarms with Polymeric Hands Catching Bacteria and Microplastics in Water.
ACS nano
May 8, 2024
The forefront of micro- and nanorobot research involves the development of smart swimming micromachines emulating the complexity of natural systems, such as the swarming and collective behaviors typically observed in animals and microorganisms, for e...
Unmasking the sky: high-resolution PM prediction in Texas using machine learning techniques.
Journal of exposure science & environmental epidemiology
Apr 1, 2024
BACKGROUND: Although PM (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies.
Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.
Journal of exposure science & environmental epidemiology
Oct 17, 2023
BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophag...
Image-based simultaneous particle size distribution and concentration measurement of powder blend components with deep learning and machine vision.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Oct 15, 2023
This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of ...
In-line particle size measurement during granule fluidization using convolutional neural network-aided process imaging.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Aug 13, 2023
This paper presents a machine learning-based image analysis method to monitor the particle size distribution of fluidized granules. The key components of the direct imaging system are a rigid fiber-optic endoscope, a light source and a high-speed cam...
Predicting spatial variations in annual average outdoor ultrafine particle concentrations in Montreal and Toronto, Canada: Integrating land use regression and deep learning models.
Environment international
Jul 22, 2023
BACKGROUND: Concentrations of outdoor ultrafine particles (UFP; <0.1 µm) and black carbon (BC) can vary greatly within cities and long-term exposures to these pollutants have been associated with a variety of adverse health outcomes.
Deep learning image analysis models pretrained on daily objects are useful for the preliminary characterization of particulate pharmaceutical samples.
Biotechnology and bioengineering
Jul 12, 2023
Visible and subvisible particles are a quality attribute in sterile pharmaceutical samples. A common method for characterizing and quantifying pharmaceutical samples containing particulates is imaging many individual particles using high-throughput i...
Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales.
International journal of pharmaceutics
May 20, 2023
The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and da...
Considering inelasticity in the real-time monitoring of particle size for twin-screw granulation via acoustic emissions.
International journal of pharmaceutics
Apr 11, 2023
A recently developed process analytical technology (PAT) using artificial intelligence to form the framework of its model, combining frequency-domain acoustic emissions (AE) and elastic impact mechanics to accurately predict complex particle size dis...
Prediction of attachment efficiency using machine learning on a comprehensive database and its validation.
Water research
Nov 25, 2022
Colloidal particles can attach to surfaces during transport, but the attachment depends on particle size, hydrodynamics, solid and water chemistry, and particulate matter. The attachment is quantified in filtration theory by measuring attachment or s...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31964
- Neural Networks, Computer 30201
- Algorithms 27375
- Deep Learning 26880
- Artificial Intelligence 24817
- Robotics 13382
- Image Processing, Computer-Assisted 9730
- Retrospective Studies 9328
- Magnetic Resonance Imaging 6341
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4863
- Support Vector Machine 4762
- Computational Biology 4328
- Brain 4125
- Computer Simulation 3932
Recent Journals
- Scientific reports 6689
- Sensors (Basel, Switzerland) 4794
- PloS one 4186
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1167
- Journal of chemical information and modeling 1059
- Nature communications 1029
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 872
- Journal of medical Internet research 853
- Briefings in bioinformatics 853