Institutional hurdles to AI for medicine began to fall, setting the stage for widespread clinical use of deep learning in medical devices and treatments. DeepMind’s AlphaFold model determined the three-dimensional shape of a protein in just hours.
Institutional hurdles to AI for medicine began to fall, setting the stage for widespread clinical use of deep learning in medical devices and treatments. DeepMind’s AlphaFold model determined the three-dimensional shape of a protein in just hours.
AI accelerated the search for a coronavirus vaccine, detected Covid-19 cases, and otherwise softened the pandemic’s blow. Machine learning researchers worldwide scrambled to harness the technology against the coronavirus.
AI accelerated the search for a coronavirus vaccine, detected Covid-19 cases, and otherwise softened the pandemic’s blow. Machine learning researchers worldwide scrambled to harness the technology against the coronavirus.
Covid Moonshot, an open-source project to vet potential medicines using machine learning, is closing in on compounds that might help curb Covid-19. Four new antiviral drugs identified by the project are ready to advance to animal trials.
Covid Moonshot, an open-source project to vet potential medicines using machine learning, is closing in on compounds that might help curb Covid-19. Four new antiviral drugs identified by the project are ready to advance to animal trials.
It’s expensive to pay doctors to label medical images, and the relative scarcity of high-quality training examples can make it hard for neural networks to learn features that make for accurate diagnoses.
It’s expensive to pay doctors to label medical images, and the relative scarcity of high-quality training examples can make it hard for neural networks to learn features that make for accurate diagnoses.
Will we ever understand what goes on inside the mind of a neural network?The fear: When AI systems go wrong, no one will be able to explain the reasoning behind their decisions.
Will we ever understand what goes on inside the mind of a neural network?The fear: When AI systems go wrong, no one will be able to explain the reasoning behind their decisions.
Controversy erupted over the need for transparency in research into AI for medicine. Google Health introduced a system that purportedly identified breast cancer more accurately than human radiologists.
Controversy erupted over the need for transparency in research into AI for medicine. Google Health introduced a system that purportedly identified breast cancer more accurately than human radiologists.
New guidelines for reporting on experiments with medical AI aim to ensure that such research is transparent, rigorous, and reliable. Spirit-AI and Consort-AI are complementary protocols designed to improve the quality of clinical trials for AI-based interventions.
New guidelines for reporting on experiments with medical AI aim to ensure that such research is transparent, rigorous, and reliable. Spirit-AI and Consort-AI are complementary protocols designed to improve the quality of clinical trials for AI-based interventions.
Convolutional neural networks are good at recognizing disease symptoms in medical scans of patients who were injected with iodine-based dye, that makes their organs more visible. But some patients can’t take the dye. Now synthetic scans from a GAN are helping CNNs learn to analyze undyed images.
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