A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...
The inaugural season of the Gomezgil Yaspik Data Science Laboratory marks the beginning of a new chapter for for Bowdoin.
Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.
Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...
A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
Key market opportunities in AI for omics studies include the demand for precision medicine, adoption of AI in drug discovery, ...
Managing a medical supply chain in low- and middle-income countries can mean navigating a landscape prone to extreme and ...
Vensure reduced security data costs by $250K annually while improving threat detection through AI-powered log filtering ...
Lee Kang-wook, Chief AI Officer (CAIO) at KRAFTON, presented a new agenda for game AI at one of the world's most prestigious ...
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