AI fighting breast cancer.
According to the WHO, breast cancer has recently overtaken lung cancer to become the most common cancer globally. The BreastPathQ Challenge was launched at the SPIE Medical Imaging 2019 conference to support the development of computer-aided diagnosis for assessing breast cancer pathology. 39 teams from 12 countries participated, with 100 new algorithms developed.
The exciting results and ideas produced by the challenge have recently been reported in the Journal of Medical Imaging: https://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-8/issue-03/034501/SPIE-AAPM-NCI-BreastPathQ-challenge--an-image-analysis-challenge/10.1117/1.JMI.8.3.034501.full?SSO=1
#sciencenews #AI #ML #healthcare #medicine
According to the WHO, breast cancer has recently overtaken lung cancer to become the most common cancer globally. The BreastPathQ Challenge was launched at the SPIE Medical Imaging 2019 conference to support the development of computer-aided diagnosis for assessing breast cancer pathology. 39 teams from 12 countries participated, with 100 new algorithms developed.
The exciting results and ideas produced by the challenge have recently been reported in the Journal of Medical Imaging: https://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-8/issue-03/034501/SPIE-AAPM-NCI-BreastPathQ-challenge--an-image-analysis-challenge/10.1117/1.JMI.8.3.034501.full?SSO=1
#sciencenews #AI #ML #healthcare #medicine
www.spiedigitallibrary.org
SPIE-AAPM-NCI BreastPathQ Challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer…
The <i>Journal of Medical Imaging</i> allows for the peer-reviewed communication and archiving of fundamental and translational research, as well as applications, focused on medical imaging, a field that continues to benefit from technological improvements…
Deep Neural Networks in medical imaging.
Scientists at the University of California are investigating how neural networks can be used to efficiently and accurately analyse associations between gene expression and features of biological tissues. They consider how the neural networks could lead to improvements in lung cancer diagnosis.
The results are published in the Journal of Medical Imaging: https://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-8/issue-03/031906/Using-deep-neural-networks-and-interpretability-methods-to-identify-gene/10.1117/1.JMI.8.3.031906.full
#sciencenews #AI #ML #healthcare #medicine
Scientists at the University of California are investigating how neural networks can be used to efficiently and accurately analyse associations between gene expression and features of biological tissues. They consider how the neural networks could lead to improvements in lung cancer diagnosis.
The results are published in the Journal of Medical Imaging: https://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-8/issue-03/031906/Using-deep-neural-networks-and-interpretability-methods-to-identify-gene/10.1117/1.JMI.8.3.031906.full
#sciencenews #AI #ML #healthcare #medicine
www.spiedigitallibrary.org
Using deep neural networks and interpretability methods to identify gene expression patterns that predict radiomic features and…
The <i>Journal of Medical Imaging</i> allows for the peer-reviewed communication and archiving of fundamental and translational research, as well as applications, focused on medical imaging, a field that continues to benefit from technological improvements…