By Shania Kennedy, contributing writer for Healthitanalytics.com
In a study published in Critical Care Medicine, researchers found that retraining and recalibration of a machine learning (ML)-based clinical decision support tool to predict readmission or death within seven days after discharge from the intensive care unit (ICU) significantly improved prediction performance, highlighting the importance of external validation and retraining before applying models in new settings.
By Dhanshree Shripad Shenwai, contributing writer for Marktechpost.com
Machine Learning (ML) models are data sets that have been taught to identify specific occurrences. The trained model may then generate inferences and predictions about data it has never seen before. Machine learning requires reliable outcomes from an automated decision or assessment process. It is also challenging, if possible, to provide a clear description of the answer or the criteria used to make a choice.
By Ajay Khanna, contributing writer for Risnews.com
Within the last 10 years, the retail industry has experienced an unprecedented digital transformation, further supercharged by the pandemic. In fact, since the pandemic began in 2020, e-commerce has grown two to five times faster than years previous, and in 2022, global e-commerce sales were expected to reach $5.5 trillion.
By Haziqa Sajid, contributing writer for Unite.ai
Terminologies like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning are hype these days. People, however, often use these terms interchangeably. Although these terms highly co-relate with each other, they also have distinctive features and specific use cases.
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