Learning a high-dimensional classification rule using auxiliary outcomes

Correlated outcomes are common in many practical problems. Based on a decomposition of estimation bias into two types, within-subspace and against-subspace, we develop a robust approach to estimating the classification rule for the outcome of interest with the presence of auxiliary outcomes in high-dimensional settings. The proposed method includes a pooled estimation step using all outcomes to gain efficiency, and a subsequent calibration step using only the outcome of interest to correct both types of biases. We show that when the pooled estimator has a low estimation error and a sparse against-subspace bias, the calibrated estimator can achieve a lower estimation error than that when using only the single outcome of interest. An inference procedure for the calibrated estimator is also provided. Simulations and a real data analysis are conducted to justify the superiority of the proposed method.Comment: 19 pages, 3 figure

Image Registration of In Vivo Micro-Ultrasound and Ex Vivo Pseudo-Whole Mount Histopathology Images of the Prostate: A Proof-of-Concept Study

Early diagnosis of prostate cancer significantly improves a patient's 5-year survival rate. Biopsy of small prostate cancers is improved with image-guided biopsy. MRI-ultrasound fusion-guided biopsy is sensitive to smaller tumors but is underutilized due to the high cost of MRI and fusion equipment. Micro-ultrasound (micro-US), a novel high-resolution ultrasound technology, provides a cost-effective alternative to MRI while delivering comparable diagnostic accuracy. However, the interpretation of micro-US is challenging due to subtle gray scale changes indicating cancer vs normal tissue. This challenge can be addressed by training urologists with a large dataset of micro-US images containing the ground truth cancer outlines. Such a dataset can be mapped from surgical specimens (histopathology) onto micro-US images via image registration. In this paper, we present a semi-automated pipeline for registering in vivo micro-US images with ex vivo whole-mount histopathology images. Our pipeline begins with the reconstruction of pseudo-whole-mount histopathology images and a 3-dimensional (3D) micro-US volume. Each pseudo-whole-mount histopathology image is then registered with the corresponding axial micro-US slice using a two-stage approach that estimates an affine transformation followed by a deformable transformation. We evaluated our registration pipeline using micro-US and histopathology images from 18 patients who underwent radical prostatectomy. The results showed a Dice coefficient of 0.94 and a landmark error of 2.7 mm, indicating the accuracy of our registration pipeline. This proof-of-concept study demonstrates the feasibility of accurately aligning micro-US and histopathology images. To promote transparency and collaboration in research, we will make our code and dataset publicly available

Research on the takeaway food safety around the university town based on the takeout catering APP

A sample survey was conducted on the qualifications of take-out catering,food safety files,holding of three certificates,and the evaluation of their packaging materials and seals was given as well.Taking the University City of the Three Universities in Shanghai Bay as an example,three take-away foods with the highest order rates around the university city were selected by online questionnaires.And the total number of colonies and the number of coliforms of the three foods were studied.The results show that the safety of take-out catering around the university city needs to be improved.This survey provides data support for the effective prevention and supervision of take-out catering around the university town.And suggestions for healthy eating,food safety,and the healthy development of the online food delivery industry were provided based on this study

On the effect of electronic patient portal on primary care utilization and appointment adherence

Abstract Background The objective of this study was to investigate the impact of patient portal adoption on patients’ primary care utilization and appointment adherence. Methods We conducted a retrospective observational study using a panel difference-in-differences (DID) framework to investigate the use of primary care services by patients, adjusting for their disease burden and allowing for time-dependent portal effect. A large dataset with 46,544 patients of University of Florida (UF) Health during the study period July 2013 – June 2016 was used. The main outcome measures are disease burden adjusted rates of office visits arrived, no-show, and cancellation to primary care physicians (PCPs) per quarter between patient portal adopters (denoted as users) and non-users. Results At the time of adoption, the quarterly PCP office visit rate ratio (RR) of patient portal users to non-users was 1.33 (95% CI, 1.27–1.39; p  0.05 for all cases). Conclusions Patient portal users’ disease burden adjusted PCP office visit rate was significantly reduced in one and a half year and thereafter post portal adoption. PCP appointment no-show rate was also significantly reduced and cancellation rate was not affected, implying improved care engagement of patients