Machine learning in the clinical microbiology laboratory: has the time come for routine practice?
Background Machine learning (ML) allows the analysis of complex and large data sets and
has the potential to improve health care. The clinical microbiology laboratory, at the interface …
has the potential to improve health care. The clinical microbiology laboratory, at the interface …
Controlled-channel attacks: Deterministic side channels for untrusted operating systems
Y Xu, W Cui, M Peinado - 2015 IEEE Symposium on Security …, 2015 - ieeexplore.ieee.org
The presence of large numbers of security vulnerabilities in popular feature-rich commodity
operating systems has inspired a long line of work on excluding these operating systems …
operating systems has inspired a long line of work on excluding these operating systems …
Advances towards automatic detection and classification of parasites microscopic images using deep convolutional neural network: methods, models and research …
In the develo** world, parasites are responsible for causing several serious health
problems, with relatively high infections in human beings. The traditional manual light …
problems, with relatively high infections in human beings. The traditional manual light …
Deep convolutional neural networks for microscopy-based point of care diagnostics
Point of care diagnostics using microscopy and computer vision methods have been applied
to a number of practical problems, and are particularly relevant to low-income, high disease …
to a number of practical problems, and are particularly relevant to low-income, high disease …
Parasitic egg recognition using convolution and attention network
Intestinal parasitic infections (IPIs) caused by protozoan and helminth parasites are among
the most common infections in humans in low-and-middle-income countries. IPIs affect not …
the most common infections in humans in low-and-middle-income countries. IPIs affect not …
Detection of intestinal protozoa in trichrome-stained stool specimens by use of a deep convolutional neural network
BA Mathison, JL Kohan, JF Walker… - Journal of clinical …, 2020 - Am Soc Microbiol
Intestinal protozoa are responsible for relatively few infections in the developed world, but
the testing volume is disproportionately high. Manual light microscopy of stool remains the …
the testing volume is disproportionately high. Manual light microscopy of stool remains the …
Methods for quantification of soil-transmitted helminths in environmental media: current techniques and recent advances
Limiting the environmental transmission of soil-transmitted helminths (STHs), which infect
1.5 billion people worldwide, will require sensitive, reliable, and cost-effective methods to …
1.5 billion people worldwide, will require sensitive, reliable, and cost-effective methods to …
Automatic segmentation and classification of human intestinal parasites from microscopy images
Human intestinal parasites constitute a problem in most tropical countries, causing death or
physical and mental disorders. Their diagnosis usually relies on the visual analysis of …
physical and mental disorders. Their diagnosis usually relies on the visual analysis of …
[HTML][HTML] A historical review of the techniques of recovery of parasites for their detection in human stools
FA Soares, AN Benitez, BM Santos… - Revista da Sociedade …, 2020 - SciELO Brasil
Since the early 20th century, the detection of intestinal parasites has improved with the
development of several techniques for parasitic structures recovery and identification, which …
development of several techniques for parasitic structures recovery and identification, which …
Automatic recognition of parasitic products in stool examination using object detection approach
Background Object detection is a new artificial intelligence approach to morphological
recognition and labeling parasitic pathogens. Due to the lack of equipment and trained …
recognition and labeling parasitic pathogens. Due to the lack of equipment and trained …