Who's Next: Rising Star Prediction via Diffusion of User Interest in Social Networks

Finding items with potential to increase sales is of great importance in online market. In this paper, we propose to study this novel and practical problem: rising star prediction. We call these potential items Rising Star , which implies their ability to rise from low-turnover items to best-sellers in the future. Rising stars can be used to help with unfair recommendation in e-commerce platform, balance supply and demand to benefit the retailers and allocate marketing resources rationally. Although the study of rising star can bring great benefits, it also poses challenges to us. The sales trend of rising star fluctuates sharply in the short-term and exhibits more contingency caused by some external events (e.g., COVID-19 caused increasing purchase of the face mask) than other items, which cannot be solved by existing sales prediction methods. To address above challenges, in this paper, we observe that the presence of rising stars is closely correlated with the early diffusion of user interest in social networks, which is validated in the case of Taocode (an intermediary that diffuses user interest in Taobao). Thus, we propose a novel framework, RiseNet, to incorporate the user interest diffusion process with the item dynamic features to effectively predict rising stars. Specifically, we adopt a coupled mechanism to capture the dynamic interplay between items and user interest, and a special designed GNN based framework to quantify user interest. Our experimental results on large-scale real-world datasets provided by Taobao demonstrate the effectiveness of our proposed framework.

Hospital Readmissions After Implementation of a Discharge Care Program for Patients with COVID-19 Illness.

BACKGROUND: The surge of coronavirus 2019 (COVID-19) hospitalizations in New York City required rapid discharges to maintain hospital capacity. OBJECTIVE: To determine whether lenient provisional discharge guidelines with remote monitoring after discharge resulted in safe discharges home for patients hospitalized with COVID-19 illness. DESIGN: Retrospective case series SETTING: Tertiary care medical center PATIENTS: Consecutive adult patients hospitalized with COVID-19 illness between March 26, 2020, and April 8, 2020, with a subset discharged home INTERVENTIONS: COVID-19 Discharge Care Program consisting of lenient provisional inpatient discharge criteria and option for daily telephone monitoring for up to 14 days after discharge MEASUREMENTS: Fourteen-day emergency department (ED) visits and hospital readmissions RESULTS: Among 812 patients with COVID-19 illness hospitalized during the study time period, 15.5% died prior to discharge, 24.1% remained hospitalized, 10.0% were discharged to another facility, and 50.4% were discharged home. Characteristics of the 409 patients discharged home were mean (SD) age 57.3 (16.6) years; 245 (59.9%) male; 27 (6.6%) with temperature ≥ 100.4 °F; and 154 (37.7%) with oxygen saturation < 95% on day of discharge. Over 14 days of follow-up, 45 patients (11.0%) returned to the ED, of whom 31 patients (7.6%) were readmitted. Compared to patients not referred, patients referred for remote monitoring had fewer ED visits (8.3% vs 14.1%; OR 0.60, 95% CI 0.31-1.15, p = 0.12) and readmissions (6.9% vs 8.3%; OR 1.15, 95% CI 0.52-2.52, p = 0.73). LIMITATIONS: Single-center study; assignment to remote monitoring was not randomized. CONCLUSIONS: During the COVID-19 surge in New York City, lenient discharge criteria in conjunction with remote monitoring after discharge were associated with a rate of early readmissions after COVID-related hospitalizations that was comparable to the rate of readmissions after other reasons for hospitalization before the COVID pandemic.

Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19.

BACKGROUND: Hydroxychloroquine has been widely administered to patients with Covid-19 without robust evidence supporting its use. METHODS: We examined the association between hydroxychloroquine use and intubation or death at a large medical center in New York City. Data were obtained regarding consecutive patients hospitalized with Covid-19, excluding those who were intubated, died, or discharged within 24 hours after presentation to the emergency department (study baseline). The primary end point was a composite of intubation or death in a time-to-event analysis. We compared outcomes in patients who received hydroxychloroquine with those in patients who did not, using a multivariable Cox model with inverse probability weighting according to the propensity score. RESULTS: Of 1446 consecutive patients, 70 patients were intubated, died, or discharged within 24 hours after presentation and were excluded from the analysis. Of the remaining 1376 patients, during a median follow-up of 22.5 days, 811 (58.9%) received hydroxychloroquine (600 mg twice on day 1, then 400 mg daily for a median of 5 days); 45.8% of the patients were treated within 24 hours after presentation to the emergency department, and 85.9% within 48 hours. Hydroxychloroquine-treated patients were more severely ill at baseline than those who did not receive hydroxychloroquine (median ratio of partial pressure of arterial oxygen to the fraction of inspired oxygen, 223 vs. 360). Overall, 346 patients (25.1%) had a primary end-point event (180 patients were intubated, of whom 66 subsequently died, and 166 died without intubation). In the main analysis, there was no significant association between hydroxychloroquine use and intubation or death (hazard ratio, 1.04, 95% confidence interval, 0.82 to 1.32). Results were similar in multiple sensitivity analyses. CONCLUSIONS: In this observational study involving patients with Covid-19 who had been admitted to the hospital, hydroxychloroquine administration was not associated with either a greatly lowered or an increased risk of the composite end point of intubation or death. Randomized, controlled trials of hydroxychloroquine in patients with Covid-19 are needed. (Funded by the National Institutes of Health.).