Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.
As AI Music Tools Proliferate, Detection Technologies and Industry Responses EvolveThe music industry faces an unprecedented ...
Pursuant to the Agreement, Hunan Saitumofei has granted Shanghai Benke exclusive distribution rights for the Analyzer in East China, covering Jiangsu Province, Shanghai Municipality, and Zhejiang ...
WORK Medical Technology Group LTD (Nasdaq: WOK) ("WORK Medical", the "Company" or "we"), a supplier of medical devices in China, through its subsidiary ...
The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), ...
Users can note which content they would like to view more frequently. Instagram is handing users some control in deciding what content they see. The social media giant is allowing users to have a say ...
Learn how recommendation algorithms, streaming recommendations, and social media algorithms use content recommendation ...
A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...
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