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2026

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Partnerships To Advance Patient Safety And Address Preventable Harm: Case Studies From International Health Care Leaders, Rachel Bonesteel, Robert Saunders, Tilithia Mcbride, Susan Sheridan, David W Bates, Mark Mcclellan, Charles H Kahn, Eyal Zimlichman Jan 2026

Partnerships To Advance Patient Safety And Address Preventable Harm: Case Studies From International Health Care Leaders, Rachel Bonesteel, Robert Saunders, Tilithia Mcbride, Susan Sheridan, David W Bates, Mark Mcclellan, Charles H Kahn, Eyal Zimlichman

Faculty, Staff and Students Publications

There have been notable improvements in patient safety in recent years; however, significant challenges remain in reducing the incidence of preventable patient harm. Supporting patient safety efforts is increasingly important given increasing complexity of care and changing health needs, especially with aging populations. Emerging technologies and capabilities open new possibilities to address longstanding patient safety problems. For example, predictive analytics to support provider decision-making, increased patient interest in engagement in their care, and artificial intelligence provide opportunities to further reduce harm. Many of these examples support a more proactive approach to patient safety by focusing on anticipating, predicting, and preventing …

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Guidelines For Standard Basic Notations In Applied Statistics, Abhaya Indrayan, Shivani Saini Ms Jan 2026

Guidelines For Standard Basic Notations In Applied Statistics, Abhaya Indrayan, Shivani Saini Ms

COBRA Preprint Series

Whereas some statistical notations are standard and uniformly used by different workers, many are not. Varying notations lead to confusion among the readers, particularly those engaged with applied statistics material, such as medical professionals. This communication proposes that all basic notations be standardized so that the same notations are consistently used by different authors, in different books, journals, and articles for the benefit of those who are not rigorously trained statisticians. Guidelines for such standard notations are also provided. The lead must be taken by statisticians.

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Testing The Transferability Of Ai Models For Cold-Water Coral Detection And Classification, Kyran P. Graves, Louise Allcock, David K.A. Barnes, Amelia E.H. Bridges, Kerry L. Howell Jan 2026

Testing The Transferability Of Ai Models For Cold-Water Coral Detection And Classification, Kyran P. Graves, Louise Allcock, David K.A. Barnes, Amelia E.H. Bridges, Kerry L. Howell

School of Biological and Marine Sciences

The proliferation of accessible deep-water imaging platforms has resulted in the acquisition of vast amounts of image data, resulting in an analysis bottleneck. Object detection is now being applied to assist the image annotation process, with the potential to reduce analysis time. However, for object detectors to effectively tackle the scale of the challenge, models need to be generalisable to allow the transfer between imaging platforms and in space. This study trains YOLOv5 object detection models to identify six coral morphology groups using annotated imagery collected by ROV ISIS in the UK (JC136). Model performance was tested with independent datasets …

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