#AI approach outperformed human experts (AGAIN) in identifying #cervical precancer!
A research team led by investigators from the National Institutes of Health and Global Good has developed a #deeplearning #algorithm that can analyze digital images of a woman's cervix and accurately identify precancerous changes that require medical attention. This artificial intelligence (AI) approach, called automated visual evaluation, has the potential to revolutionize cervical cancer screening, particularly in low-resource settings.
To create the algorithm, the research team used more than 60,000 cervical images from an NCI archive of photos collected during a cervical cancer screening study that was carried out in Costa Rica in the 1990s.
Overall, the algorithm performed better than all standard screening tests at predicting all cases diagnosed during the Costa Rica study. Automated visual evaluation identified precancer with greater accuracy (AUC=0.91) than a human expert review (AUC=0.69) or conventional cytology (AUC=0.71).
Paper here: https://lnkd.in/dxETi8K
#algorithms #prediction #cancer #machinelearning #cnn #transferlearning
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
A research team led by investigators from the National Institutes of Health and Global Good has developed a #deeplearning #algorithm that can analyze digital images of a woman's cervix and accurately identify precancerous changes that require medical attention. This artificial intelligence (AI) approach, called automated visual evaluation, has the potential to revolutionize cervical cancer screening, particularly in low-resource settings.
To create the algorithm, the research team used more than 60,000 cervical images from an NCI archive of photos collected during a cervical cancer screening study that was carried out in Costa Rica in the 1990s.
Overall, the algorithm performed better than all standard screening tests at predicting all cases diagnosed during the Costa Rica study. Automated visual evaluation identified precancer with greater accuracy (AUC=0.91) than a human expert review (AUC=0.69) or conventional cytology (AUC=0.71).
Paper here: https://lnkd.in/dxETi8K
#algorithms #prediction #cancer #machinelearning #cnn #transferlearning
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv