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AI-based tools enhance early sepsis detection, leveraging EMR data and machine learning for timely treatment and improved outcomes.

Lunit to unveil four oral presentations and three poster presentations at ECR 2024, highlighting Lunit INSIGHT's expansive capability, rang...

Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced the presentation of seven studies at the European Congress of Radiology (ECR) 2024, to be held in Vienna, Austria, from February 28 to March 3. Four will be presented through oral presentations and three as E-posters.

Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced the presentation of seven studies at the European Congress...

[Special thank you to Ian Kivlichan for many useful pointers (E.g. the 100+ year old Nature paper “Vox populi”) and nice feedback. �� ] High-quality data is the fuel for modern data deep learning model training. Most of task-specific labeled data comes from human annotation, such as classification task or RLHF labeling (which can be constructed as classification format) for LLM alignment training. Lots of ML techniques in the post can help with data quality, but fundamentally human data collection involves attention to details and careful execution.