Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Socioeconomic mobility and reproductive outcomes among African American and White women in the United States.

This dissertation examines the extent to which African American and White women in the United States who have experienced upward socioeconomic mobility are able to translate their achieved social class status into favorable maternal and infant health outcomes. It is comprised of three essays, each designed to investigate how changes in lifetime maternal socioeconomic position impact infant wellbeing. In Chapter 2, I argue that upwardly mobile Black women will face similar risks of giving birth to a low birthweight baby compared to chronically poor Black women due to three overarching factors: (1) pervasive structural-level racial inequalities; (2) individual-level responses to race-based discrimination; and (3) delayed childbearing. In Chapter 3, I employ data from the National Longitudinal Survey of Youth 1979 and the 1970 U.S. Census of Population and Housing to estimate the likelihood that African American and White women who were raised in or near poverty but achieved middle-class status in adulthood will give birth to a low birthweight baby. Results from a series of logistic regression analyses illustrate that for White women who grew up in families with limited financial resources, increases in family income during adulthood are associated with a lower probability of giving birth to a low birthweight baby. However, for their African American counterparts, the relationship between adult socioeconomic position and the risk of low birthweight, although also negative, is substantially weaker and fails to reach statistical significance. In Chapter 4, I utilize birth certificate and census data from a thirty-year time period, in order to estimate the extent to which Black and White women aged 10 to 29 alter the timing of their first and second births in response to fluctuating job availability. Results from fixed-effect Poisson regression models suggest that during the 1990s---a decade of considerable economic growth---young African American women, especially those aged 18 to 19, were likely to postpone childbearing in order to take advantage of improved occupational opportunities. Furthermore, the association between employment possibilities and age-, race-, and state-specific rates of first and second births cannot be explained by concurrent changes in welfare policy, incarceration rates, or abortion availability.Ph.D.Black studiesDemographyHealth and Environmental SciencesPublic healthSocial SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/124764/2/3163776.pd

Do rising tides lift all boats? Racial disparities in health across the lifecourse among middle-class African-Americans and Whites

Although racial inequalities in health are well documented, much less is known about the underlying mechanisms that create and sustain these population patterns, especially among nonpoor subgroups. Using 20 waves of data from the Panel Study of Income Dynamics (PSID), we estimate the magnitude of the Black/White gap in self-rated health among middle-income, working-age (18–65) adults and explore potential sources of this disparity. Findings from multilevel regression models suggest that intragenerational gains in family income result in significantly smaller improvements in self-rated health for middle-class African-Americans than similarly situated Whites. We also note that childhood disadvantage predicts subsequent health trajectories in adulthood, but does little to explain the Black/White gap in the association between family income and self-rated health. We conclude that middle-class status provides restricted health returns to upward mobility for African-Americans and this differential relationship cannot be accounted for by greater exposure to early life disadvantage. Keywords: Health disparities, Life course processes, African Americans, Socioeconomic mobility, Self-rated health, Childhood disadvantag

Getting a piece of the pie? The economic boom of the 1990s and declining teen birth rates in the United States

In the United States, the 1990s was a decade of dramatic economic growth as well as a period characterized by substantial declines in teenage childbearing. This study examines whether falling teen fertility rates during the 1990s were responsive to expanding employment opportunities and whether the implementation of the Personal Responsibility and Work Opportunities Act (PRWORA), increasing rates of incarceration, or restrictive abortion policies may have affected this association. Fixed-effects Poisson regression models were estimated to assess the relationship between age-specific birth rates and state-specific unemployment rates from 1990 to 1999 for Black and White females aged 10-29. Falling unemployment rates in the 1990s were associated with decreased childbearing among African-American women aged 15-24, but were largely unrelated to declines in fertility for Whites. For 18-19 year-old African-Americans, the group for whom teen childbearing is most normative, our model accounted for 85% of the decrease in rates of first births. Young Black women, especially older teens, may have adjusted their reproductive behavior to take advantage of expanded labor market opportunities.United States Teenage childbearing Fertility timing Race Social mobility Poverty

Maternal Upward Socioeconomic Mobility and Black–White Disparities in Infant Birthweight

Objectives. We estimate the extent to which upward socioeconomic mobility limits the probability that Black and White women who spent their childhoods in or near poverty will give birth to a low-birthweight baby. Methods. Data from the National Longitudinal Survey of Youth 1979 and the 1970 US Census were used to complete a series of logistic regression models. We restricted multivariate analyses to female survey respondents who, at 14 years of age, were living in households in which the income-to-needs ratio did not exceed 200% of poverty. Results. For White women, the probability of giving birth to a low-birthweight baby decreases by 48% for every 1 unit increase in the natural logarithm of adult family income, once the effects of all other covariates are taken into account. For Black women, the relation between adult family income and the probability of low birthweight is also negative; however, this association fails to reach statistical significance. Conclusions. Upward socioeconomic mobility contributes to improved birth outcomes among infants born to White women who were poor as children, but the same does not hold true for their Black counterparts