Evaluating allograft risk models in organ transplantation: Understanding and balancing model discrimination and calibration.

In the field of organ transplantation, the accurate assessment of donor organ quality is necessary to efficient organ allocation and to informed consent for recipients. A common approach to organ quality assessment is the development of statistical models that accurately predict post-transplant survival by integrating multiple characteristics of the donor and allograft. Despite the proliferation of predictive models across many domains of medicine, many physicians may have limited familiarity with how these models are built, the assessment of how well models function in their population and the risks of a poorly performing model.

Regret in Clinical Trial Participation Among Cancer Patients.

This analysis examined regret from participation in cancer clinical trials (CCT) and explored associations between regret and symptom burden, symptom bother, therapeutic optimism, and the importance of spiritual beliefs. This is a secondary analysis of cross-sectional data from a study of American CCT patient-participants conducted from 2015 to 2019. Descriptive statistics, bivariate associations, and logistic regression were used to evaluate regret in this sample ( = 325).

Kinematic signature of high risk labored breathing revealed by novel signal analysis.

Breathing patterns (respiratory kinematics) contain vital prognostic information. This dimension of physiology is not captured by conventional vital signs. We sought to determine the feasibility and utility of quantifying respiratory kinematics.

Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines.

This article describes the Cell Maps for Artificial Intelligence (CM4AI) project and its goals, methods, standards, current datasets, software tools , status, and future directions. CM4AI is the in the U.S.

Positive feedbacks and alternative stable states in forest leaf types.

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states.