Science is a subject built on doing. Students learn chemistry through titrations, biology through dissections, physics through motion experiments, and earth science through field observations. That ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?
A research team from The Hong Kong University of Science and Technology (HKUST) has developed GrainBot, an AI-enabled toolkit ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
News-Medical.Net on MSN
CNN-based system improves lung nodule detection and classification
Background and objectives Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.
11don MSN
Brain responses to wildlife images can forecast online engagement—and help conservation messaging
What types of photos make people reach for their wallets? New Stanford University-led research suggests that brain activity can help forecast which wildlife images will inspire people to engage online ...
Researchers find that "object recognition" ability, rather than intelligence or tech experience, determines who can best ...
It’s more than just code. Scientists have found a way to "dial" the hidden personalities of AI, from conspiracy theorists to ...
Researchers are using artificial intelligence to perfect the design of the vessels surrounding the super-hot plasma, optimize heating methods and maintain stable control of the reaction for ...
Tech Xplore on MSN
Reasoning: A smarter way for AI to understand text and images
Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to solve complex problems more reliably, particularly those that require ...
Live Science on MSN
'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images
Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.
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