Immunotherapy for Glioblastomas

Hu, Wanming; Shan, Frank Y.; Mukherjee, Sumitava; Levačić, Danijela; Huang, Jason H.

doi:10.5772/intechopen.91759

Cited by 7 publications

(9 citation statements)

References 44 publications

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“…After removing duplicates (ie, reposts of original posts), we retained 14,983,647 posts sent between November 1, 2019 (ie, 30 days before the first confirmed cases) and March 31, 2020 (to access the Weibo dataset on COVID-19, see [ 28 ]).…”

Section: Methodsmentioning

confidence: 99%

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Shen¹,

Chen²,

Luo³

et al. 2020

J Med Internet Res

143

108

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Background Coronavirus disease (COVID-19) has affected more than 200 countries and territories worldwide. This disease poses an extraordinary challenge for public health systems because screening and surveillance capacity is often severely limited, especially during the beginning of the outbreak; this can fuel the outbreak, as many patients can unknowingly infect other people. Objective The aim of this study was to collect and analyze posts related to COVID-19 on Weibo, a popular Twitter-like social media site in China. To our knowledge, this infoveillance study employs the largest, most comprehensive, and most fine-grained social media data to date to predict COVID-19 case counts in mainland China. Methods We built a Weibo user pool of 250 million people, approximately half the entire monthly active Weibo user population. Using a comprehensive list of 167 keywords, we retrieved and analyzed around 15 million COVID-19–related posts from our user pool from November 1, 2019 to March 31, 2020. We developed a machine learning classifier to identify “sick posts,” in which users report their own or other people’s symptoms and diagnoses related to COVID-19. Using officially reported case counts as the outcome, we then estimated the Granger causality of sick posts and other COVID-19 posts on daily case counts. For a subset of geotagged posts (3.10% of all retrieved posts), we also ran separate predictive models for Hubei province, the epicenter of the initial outbreak, and the rest of mainland China. Results We found that reports of symptoms and diagnosis of COVID-19 significantly predicted daily case counts up to 14 days ahead of official statistics, whereas other COVID-19 posts did not have similar predictive power. For the subset of geotagged posts, we found that the predictive pattern held true for both Hubei province and the rest of mainland China regardless of the unequal distribution of health care resources and the outbreak timeline. Conclusions Public social media data can be usefully harnessed to predict infection cases and inform timely responses. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. In addition to monitoring overall search and posting activities, leveraging machine learning approaches and theoretical understanding of information sharing behaviors is a promising approach to identify true disease signals and improve the effectiveness of infoveillance.

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Section: Methodsmentioning

confidence: 99%

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Shen¹,

Chen²,

Luo³

et al. 2020

J Med Internet Res

143

108

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“…For comparison purposes, we have finally detected the outliers in SDS1 and SDS2 by using some outlier detection packages in R environment. The function lofactor in the package DMwR ( Torgo, 2010 ) and the function lof in the package Rlof ( Hu et al, 2020 ) calculate local outlier factors using the LOF (local outlier factor) algorithm with the parameter k , which is the number of neighbors used in the calculation of the local outlier factors. LOF is an algorithm for identifying density-based local outliers ( Breunig et al, 2000 ).…”

Section: Comparison Of Multivariate Outlier Detection Methodsmentioning

confidence: 99%

Two novel outlier detection approaches based on unsupervised possibilistic and fuzzy clustering

Cebecí

Cebeci

Tahtali

et al. 2022

PeerJ Computer Science

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Outliers are data points that significantly deviate from other data points in a data set because of different mechanisms or unusual processes. Outlier detection is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for data cleansing in data science. In this study, we propose two novel outlier detection approaches using the typicality degrees which are the partitioning result of unsupervised possibilistic clustering algorithms. The proposed approaches are based on finding the atypical data points below a predefined threshold value, a possibilistic level for evaluating a point as an outlier. The experiments on the synthetic and real data sets showed that the proposed approaches can be successfully used to detect outliers without considering the structure and distribution of the features in multidimensional data sets.

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“…Till date, although extensive reviews on TiO 2 , [ 29 ] CdS, [ 25 ] and other core‐shell systems [ 30 ] have been reported, there are no reviews on WO 3 ‐based core‐shell systems. Considering the plethora of studies conducted on WO 3 ‐based core‐shell nanostructure systems for use in versatile applications, summarizing recent developments in structural design, processing, and performance in representative applications is warranted to guide future development.…”

Section: Introductionmentioning

confidence: 99%

Core‐Shell Engineered WO₃ Architectures: Recent Advances from Design to Applications

Adhikari

Murmu

Kim

2022

Small

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Ongoing efforts to design novel materials with efficient structure‐property‐performance relations prove challenging. Core‐shell structures have emerged as novel materials with controlled production routes and highly tailorable properties that offer extensive advantages in advanced oxidation processing, particularly in photocatalysis and photoelectrochemical applications. WO3, which is an optoelectronically active semiconductor material, is a popular material in current studies in the field of photo(electro)catalysis. Considerable progress has been made using core‐shell WO3 architectures, which warrants an evaluation in terms of processing and preparedness for their use in versatile catalytic and energy storage applications. This paper presents an in‐depth assessment of core‐shell WO3 architectures by highlighting the design challenges and protocols in powder and thin‐film chemical processing. The development of specific core‐shell designs for use in targeted applications, such as H2 production, CO2 reduction, wastewater treatment, batteries, supercapacitors, and sensing, is analyzed. The fundamental role of WO3 in core‐shell structures to enhance efficiency is also discussed, along with the limitations and improvement strategies. Further, the prospects of core‐shell WO3 architectures in energy conversion and environmental applications are suggested.

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Immunotherapy for Glioblastomas

Cited by 7 publications

References 44 publications

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Two novel outlier detection approaches based on unsupervised possibilistic and fuzzy clustering

Core‐Shell Engineered WO₃ Architectures: Recent Advances from Design to Applications

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Immunotherapy for Glioblastomas

Cited by 7 publications

References 44 publications

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Two novel outlier detection approaches based on unsupervised possibilistic and fuzzy clustering

Core‐Shell Engineered WO3 Architectures: Recent Advances from Design to Applications

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Product

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Core‐Shell Engineered WO₃ Architectures: Recent Advances from Design to Applications