Opening the “Black Box”: A Conversation with Microsoft’s Rich Caruana About AI in Health Care

Rich Caruana, senior principal researcher at Microsoft Research, has been working in machine learning in health care since the 1990s, when his graduate advisor asked him to help train a model to help a group of clinicians and scien­tists predict pneumonia risk

“Don’t Panic” – Stephen Aylward, PhD, on AI in Medical Imaging

After a decade of working in medi­cal image processing as a professor of radiology at the University of North Carolina School of Medicine, Stephen Aylward, PhD, founded the North Carolina office of the open-source soft­ware company Kitware. The company provides artificial intelligence (AI) and other advanced technical computing services to a variety of companies and conducts National Institutes of Health (NIH), Defense Advanced Research Projects Agency (DARPA), and US Department of Defense (DoD) grant-funded research on medical imaging, scientific computing, and computer vision

Artificial Intelligence in Health Care: Opportunities, Challenges, and the Road Ahead

A comprehensive, collective approach to navigating the challenges of bias, privacy, and ethical considerations presented by the use of artificial intelligence in health care will require robust frameworks, continuous learning, and a commitment to equity. The insights and discussions presented in this issue are a testament to the ongoing efforts in North Carolina and beyond to find a balance between innovation with responsibility, ensuring that AI can deliver on its promise to enhance outcomes

Older adults’ spirituality and life satisfaction: a longitudinal test of social support and sense of coherence as mediating mechanisms

Spirituality is proposed to be a component of successful ageing and has been shown to predict wellbeing in old age. There has been conceptual discussion of possible mechanisms that link spirituality with positive psychological functioning in older adults, but few empirical examinations of these linking mechanisms over time. The current study examined the role of Antonovsky's Sense of Coherence (SOC) and social support in mediating the effects of spirituality on life satisfaction in older participants over a four-year period. The study used a cross-lagged panel analysis to evaluate longitudinal mediation within a path analysis framework. Results showed that the meaningfulness dimension of SOC mediated the influence of spirituality on life satisfaction over time, suggesting that spirituality may influence older adults' experience and perception of life events, leading to a more positive appraisal of these events as meaningful. Social support was not found to mediate the pathway between spirituality and life satisfaction. This study may be the first to examine the link between spirituality, sense of coherence, social support and wellbeing, as measured by life satisfaction, using longitudinal data from a community sample of older adults. The study provides evidence for the positive role of spirituality in the lives of older people. This is an area that requires further examination in models of successful ageing

Cropland Cash Rental Rates in the Upper Mississippi River Basin

The report documents the creation of estimates for cropland cash rental rates in the Upper Mississippi River Basin in 1997. Although the basic data come from disparate sources, we employ a unifying estimation procedure based on the presumption that the cropland cash rental rate is an increasing function of corn yield potential. The rates are estimated at some 42,000 National Resources Inventory data points representing cropland in Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin

Managerial Incentives in Public Service Delivery: Evidence from School-based Nutrition Programs in Rural China

Growing evidence indicates that weak or misaligned incentives facing providers pose a significant barrier to service delivery in many developing countries. To address weak supply-side incentives, performance pay and related approaches explicitly linking provider pay and performance have become increasingly common in public service delivery. Despite the growing prominence of these approaches, however, many conceptual issues surrounding the use of performance pay in this context remain unexplored. A fundamental one is the role of performance pay for managers in the organizations commonly tasked with delivering public services. Although a large literature examines performance pay for managers in private firms, much less is known about the use of performance pay for their counterparts in public service organizations. Improving public service delivery may nonetheless depend heavily on aligning the incentives of managers with social objectives. Drawing on a large-scale field experiment involving 300 primary schools in rural China, this dissertation explores how performance incentives for school administrators affect their implementation of new, school-based nutrition programs targeting anemia. School-based nutrition programs are an important function of schools, particularly in settings with less developed public health infrastructures. Weak incentives for schools to effectively implement these programs are compounded as these programs compete with more traditional functions for finite school resources. I report the results of this field experiment which was designed to test three main issues concerning the use of performance incentives for school administrators in this context. First, I study the effect of offering administrators performance pay contracts tied to reductions in school-level anemia prevalence. As part of the experiment, a subset of schools were randomly allocated to receive one of two levels of performance incentives for reductions in student anemia or to a no-incentive comparison group. I find that large incentives led to meaningful reductions while smaller incentives (10% of the size) were ineffective in reducing anemia. Further, I find that an important channel through which large incentives impacted student nutrition was by motivating administrators to engage households and influence feeding at home. I discuss the implications of this finding for the design of performance incentives tied to jointly produced outcomes. Second, I study the impact of providing administrators with more resources to implement a nutrition program and how this interacts with performance incentives. To test this, schools were orthogonally assigned to two levels of block grants within each level of performance incentives. I find that, absent explicit anemia-based incentives, increasing the size of block grants under the control of administrators led to sizable reductions in anemia prevalence but were nearly twice as costly as performance incentives. This impact was not purely the result of additional inputs; larger block grants also caused a more efficient use of inputs and an increase in effort devoted to reducing anemia. I also find that additional resources and incentives are substitutes in this context. I provide evidence that this substitution is due, at least in part, to incentives re-framing the task of implementing the nutrition programs from one that was part of the professional role of administrators to one that was not. Finally, I approach the health promotion and education roles of schools as a multi-tasking problem and use remaining experimental groups to examine how performance incentives for school administrators to reduce anemia and improve test scores each affect anemia prevalence and academic performance. Although the theory of multitasking is well-developed, there are few empirical studies testing this theory directly. I emphasize three main findings. First, incentives in the two dimensions (given in the context of an anemia reduction program) both led to significant reductions in anemia prevalence. Second, anemia-based and test-based incentives serve as substitutes in the direction of anemia reduction: providing administrators with both types of incentives did not lead to significantly larger reductions in anemia. Third, I find that anemia incentives caused an allocation of resources away from education 'inputs' but this did not lead to significantly lower student performance on standardized exams after one year. These results reflect that test-based incentives are well-aligned with improving nutrition, but anemia-based incentives are not well aligned with effort to improve academic performance. Strengthening incentives to improve academic performance while also emphasizing the relationship between good nutrition and academic performance may therefore be sufficient to motivate administrators to effectively implement school-based anemia reduction programs while causing less reallocation of resources away from education

TRAIL-induced variation of cell signaling states provides nonheritable resistance to apoptosis.

TNFα-related apoptosis-inducing ligand (TRAIL), specifically initiates programmed cell death, but often fails to eradicate all cells, making it an ineffective therapy for cancer. This fractional killing is linked to cellular variation that bulk assays cannot capture. Here, we quantify the diversity in cellular signaling responses to TRAIL, linking it to apoptotic frequency across numerous cell systems with single-cell mass cytometry (CyTOF). Although all cells respond to TRAIL, a variable fraction persists without apoptotic progression. This cell-specific behavior is nonheritable where both the TRAIL-induced signaling responses and frequency of apoptotic resistance remain unaffected by prior exposure. The diversity of signaling states upon exposure is correlated to TRAIL resistance. Concomitantly, constricting the variation in signaling response with kinase inhibitors proportionally decreases TRAIL resistance. Simultaneously, TRAIL-induced de novo translation in resistant cells, when blocked by cycloheximide, abrogated all TRAIL resistance. This work highlights how cell signaling diversity, and subsequent translation response, relates to nonheritable fractional escape from TRAIL-induced apoptosis. This refined view of TRAIL resistance provides new avenues to study death ligands in general

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity.

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple ([Formula: see text]40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples