Abstract: Federated learning is an emerging machine learning paradigm that effectively alleviates the data silo problem by distributing the model training process to multiple data holders. However, ...
A new study finds that large language models (LLMs), used with straightforward prompting, perform poorly on routine ...
Molecular pathology has entered a transformative era under the influence of artificial intelligence (AI). The intersection of digital pathology, molecular ...
Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
Since 2007, Jezebel has been the Internet's most treasured source for everything celebrities, sex, and politics...with teeth.
With the rapid expansion of the new energy vehicle (NEV) market, charging and battery swapping have emerged as the two ...
Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...
Million Records Built from Live Attack Traffic Released to Advance Cybersecurity Research at the University of ...
Abstract: Single positive multi-label learning (SPML) aims to recognize multiple categories with limited supervision from one positive label in an image. With the emergence of pre-trained ...
As AI becomes a daily work tool, the real risk may not be losing our intelligence—but losing confidence in our own thinking. New research suggests the difference comes down to how actively we engage ...
No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)–based models may be the solution ...
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