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Doctoral student’s system eases patient-discharge process

Doctoral student’s system eases patient-discharge process

Every day, millions of people are discharged after extended hospital stays, but matching these patients with appropriate care facilities can be arduous, often reliant on months-old, inaccurate data.

Now, a text message-based, hybrid computer-human system that regularly updates both patients’ and care facilities’ availability statuses, developed by a Cornell doctoral student, is smoothing that time-consuming process. The system was tested at a hospital in Hawaii for 14 months, beginning in early 2022, and helped place nearly 50 patients in care facilities.

Using AI to learn quantum complexity

Using AI to learn quantum complexity

Cornell physicists and computer scientists have developed a machine learning architecture inspired by the large language models (LLMs) behind ChatGPT to help them study the vastly complicated interactions that happen when nature’s smallest particles interact.