Adaptive conformal classification with noisy labels

This paper develops novel conformal prediction methods for classification tasks that can automatically adapt to random label contamination in the calibration sample, enabling more informative prediction sets with stronger coverage guarantees compared to state-of-the-art approaches. This is made possible by a precise theoretical characterization of the effective coverage inflation (or deflation) suffered by standard conformal inferences in the presence of label contamination, which is then made actionable through new calibration algorithms. Our solution is flexible and can leverage different modeling assumptions about the label contamination process, while requiring no knowledge about the data distribution or the inner workings of the machine-learning classifier. The advantages of the proposed methods are demonstrated through extensive simulations and an application to object classification with the CIFAR-10H image data set.Comment: 35 pages (98 pages including references and appendices

Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data

COVID-19 has a spectrum of disease severity, ranging from asymptomatic to requiring hospitalization. Understanding the mechanisms driving disease severity is crucial for developing effective treatments and reducing mortality rates. One way to gain such understanding is using a multi-class classification framework, in which patients' biological features are used to predict patients' severity classes. In this severity classification problem, it is beneficial to prioritize the identification of more severe classes and control the "under-classification" errors, in which patients are misclassified into less severe categories. The Neyman-Pearson (NP) classification paradigm has been developed to prioritize the designated type of error. However, current NP procedures are either for binary classification or do not provide high probability controls on the prioritized errors in multi-class classification. Here, we propose a hierarchical NP (H-NP) framework and an umbrella algorithm that generally adapts to popular classification methods and controls the under-classification errors with high probability. On an integrated collection of single-cell RNA-seq (scRNA-seq) datasets for 864 patients, we explore ways of featurization and demonstrate the efficacy of the H-NP algorithm in controlling the under-classification errors regardless of featurization. Beyond COVID-19 severity classification, the H-NP algorithm generally applies to multi-class classification problems, where classes have a priority order

Cumulative Exposure to Ideal Cardiovascular Health and Incident Diabetes in a Chinese Population: The Kailuan Study

Background: It is unclear whether ideal cardiovascular health (CVH), and particularly cumulative exposure to ideal CVH (cumCVH), is associated with incident diabetes. We aimed to fill this research gap. Methods and Results: The Kailuan Study is a prospective cohort of 101 510 adults aged 18 to 98 years recruited in 2006-2007 and who were subsequently followed up at 2- (Exam 2), 4- (Exam 3), and 6 (Exam 4)-year intervals after baseline. The main analysis is restricted to those individuals with complete follow-up at all 4 examinations and who had no history of diabetes until Exam 3. Cumulative exposure to ideal CVH (cumCVH) was calculated as the summed CVH score for each examination multiplied by the time between the 2 examinations (score×year). Logistic regression models were used to assess the association between cumCVH and incident diabetes. In fully adjusted models, compared with the lowest quintile of cumCVH, individuals in the highest quintile had ~68% (95% confidence interval [CI] 60-75) lower risk for incident diabetes (compared with 61% [95% CI 52-69] lower risk when using baseline CVH). Every additional year lived with a 1-unit increase in ideal CVH was associated with a 24% (95% CI 21-28) reduction in incident diabetes. Conclusions: Ideal CVH is associated with a reduced incidence of diabetes, but the association is likely to be underestimated if baseline measures of CVH exposure are used. Measures of cumulative exposure to ideal CVH are more likely to reflect lifetime risk of diabetes and possibly other health outcomes. CLINICAL TRIAL REGISTRATION: URL: https://www.chictr.org. Unique identifier: ChiCTRTNC-11001489

Attaching DNA to Nanoceria: Regulating Oxidase Activity and Fluorescence Quenching

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Applied Materials and Interfaces copyright © American Chemical Society after peer review and technical editing by publisher. To access the final edited and published work see Pautler, R., Kelly, E. Y., Huang, P.-J. J., Cao, J., Liu, B., & Liu, J. (2013). Attaching DNA to Nanoceria: Regulating Oxidase Activity and Fluorescence Quenching. ACS Applied Materials & Interfaces, 5(15), 6820–6825. https://doi.org/10.1021/am4018863Cerium oxide nanoparticles (nanoceria) have recently emerged as a nanozyme with oxidase activity. In this work, we present a few important interfacial properties of nanoceria. First, the surface charge of nanoceria can be controlled not only by adjusting pH but also by adsorption of simple inorganic anions. Adsorption of phosphate and citrate gives negatively charged surface over a broad pH range. Second, nanoceria adsorbs DNA via the DNA phosphate backbone in a sequence-independent manner; DNA adsorption inhibits its oxidase activity. Other anionic polymers display much weaker inhibition effects. Adsorption of simple inorganic phosphate does not have the inhibition effect. Third, nanoceria is a quencher for many fluorophores. These discoveries provide an important understanding for further use of nanoceria in biosensor development, materials science, and nanotechnology.University of Waterloo || Canadian Foundation for Innovation || Natural Sciences and Engineering Research Council || Ontario Ministry of Research and Innovation |

Opportunities, challenges and systems requirements for developing post-abortion family planning services: Perceptions of service stakeholders in China

Post-abortion family planning (PAFP) has been proposed as a key strategy to decrease unintended pregnancy and repeat induced abortions. However, the accessibility and quality of PAFP services remain a challenge in many countries including China where more than 10 million unintended pregnancies occur each year. Most of these unwanted pregnancies end in repeated induced abortions. This paper aims to explore service providers’ perceptions of the current situation regarding family planning and abortion service needs, provision, utilization, and the feasibility and acceptability of high quality PAFP in the future. Qualitative methods, including in-depth interviews and focus group discussions, were used with family planning policy makers, health managers, and service providers. Three provinces—Zhejiang, Hubei and Yunnan—were purposively selected, representing high, medium and relatively undeveloped areas of China. A total of fifty-three in-depth interviews and ten focus-group discussions were conducted and analysed thematically. Increased numbers of abortions among young, unmarried women were perceived as a major reason for high numbers of abortions. Participants attributed this to increasing socio-cultural acceptability of premarital sex, and simultaneously, lack of understanding or awareness of contraception among young people. The majority of service stakeholders acknowledged that free family planning services were neither targeted at, nor accessible to unmarried people. The extent of PAFP provision is variable and limited. However, service providers expressed willingness and enthusiasm towards providing PAFP services in the future. Three main considerations were expressed regarding the feasibility of developing and implementing PAFP services: policy support, human resources, and financial resources. The study indicated that key service stakeholders show demand for and perceive considerable opportunities to develop PAFP in China. However, changes are needed to enable the systematic development of high quality PAFP, including actively targeting young and unmarried people in service provision, obtaining policy support and increasing the investment of human and financial resources