arXiv subjects

Zhe He

Publications and source records attributed to Zhe He.

48 records · Page 3Linked to original sources

arXiv2019

Analyzing Social Media Data to Understand Consumers' Information Needs on Dietary Supplements

Despite the high consumption of dietary supplements (DS), there are not many reliable, relevant, and comprehensive online resources that could satisfy information seekers. The purpose of this research study is to understand consumers' information needs on DS using topic modeling and to evaluate its accuracy in correctly identifying topics from social media. We retrieved 16,095 unique questions posted on Yahoo! Answers relating to 438 unique DS ingredients mentioned in sub-section, "Alternative medicine" under the section, "Health". We implemented an unsupervised topic modeling method, Correlation Explanation (CorEx) to unveil the various topics consumers are most interested in. We manually reviewed the keywords of all the 200 topics generated by CorEx and assigned them to 38 health-related categories, corresponding to 12 higher-level groups. We found high accuracy (90-100%) in identifying questions that correctly align with the selected topics. The results could be used to guide us to generate a more comprehensive and structured DS resource based on consumers' information needs.

cs.CY↗

arXiv2019

Understanding Perceptions and Attitudes in Breast Cancer Discussions on Twitter

Among American women, the rate of breast cancer is only second to lung cancer. An estimated 12.4% women will develop breast cancer over the course of their lifetime. The widespread use of social media across the socio-economic spectrum offers unparalleled ways to facilitate information sharing, in particular as it pertains to health. Social media is also used by many healthcare stakeholders, ranging from government agencies to healthcare industry, to disseminate health information and to engage patients. The purpose of this study is to investigate people's perceptions and attitudes relate to breast cancer, especially those that are related to physical activities, on Twitter. To achieve this, we first identified and collected tweets related to breast cancer; and then used topic modeling and sentiment analysis techniques to understanding discussion themes and quantify Twitter users' perceptions and emotions w.r.t breast cancer to answer 5 research questions.

cs.CY↗

arXiv2019

Enhancing Prediction Models for One-Year Mortality in Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome

Predicting the risk of mortality for patients with acute myocardial infarction (AMI) using electronic health records (EHRs) data can help identify risky patients who might need more tailored care. In our previous work, we built computational models to predict one-year mortality of patients admitted to an intensive care unit (ICU) with AMI or post myocardial infarction syndrome. Our prior work only used the structured clinical data from MIMIC-III, a publicly available ICU clinical database. In this study, we enhanced our work by adding the word embedding features from free-text discharge summaries. Using a richer set of features resulted in significant improvement in the performance of our deep learning models. The average accuracy of our deep learning models was 92.89% and the average F-measure was 0.928. We further reported the impact of different combinations of features extracted from structured and/or unstructured data on the performance of the deep learning models.

cs.LG↗

arXiv2019

A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation

Spectral unmixing is an important and challenging problem in hyperspectral data processing. This topic has been extensively studied and a variety of unmixing algorithms have been proposed in the literature. However, the lack of publicly available dataset with ground-truth makes it difficult to evaluate and compare the performance of unmixing algorithms in a quantitative and objective manner. Most of the existing works rely on the use of numerical synthetic data and an intuitive inspection of the results of real data. To alleviate this dilemma, in this study, we design several experimental scenes in our laboratory, including printed checkerboards, mixed quartz sands, and reflection with a vertical board. A dataset is then created by imaging these scenes with the hyperspectral camera in our laboratory, providing 36 mixtures with more than 130, 000 pixels with 256 wavelength bands ranging from 400nm to 1000nm. The experimental settings are strictly controlled so that pure material spectral signatures and material compositions are known. To the best of our knowledge, this dataset is the first publicly available dataset created in a systematic manner with ground-truth for spectral unmixing. Some typical linear and nonlinear unmixing algorithms are also tested with this dataset and lead to meaningful results.

cs.CV↗

arXiv2018

Building Computational Models to Predict One-Year Mortality in ICU Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome

Heart disease remains the leading cause of death in the United States. Compared with risk assessment guidelines that require manual calculation of scores, machine learning-based prediction for disease outcomes such as mortality can be utilized to save time and improve prediction accuracy. This study built and evaluated various machine learning models to predict one-year mortality in patients diagnosed with acute myocardial infarction or post myocardial infarction syndrome in the MIMIC-III database. The results of the best performing shallow prediction models were compared to a deep feedforward neural network (Deep FNN) with back propagation. We included a cohort of 5436 admissions. Six datasets were developed and compared. The models applying Logistic Model Trees (LMT) and Simple Logistic algorithms to the combined dataset resulted in the highest prediction accuracy at 85.12% and the highest AUC at .901. In addition, other factors were observed to have an impact on outcomes as well.

cs.LG↗

arXiv2018

Quantum plasmonic hot-electron injection in lateral WSe2/MoSe2 heterostructures

Lateral two-dimensional (2D) transitional metal dichalcogenide (TMD) heterostructures have recently attracted a wide attention as promising materials for optoelectronic nanodevices. Due to the nanoscale width of lateral heterojunctions, the study of their optical properties is challenging and requires using subwavelength optical characterization techniques. We investigated the photoresponse of a lateral 2D WSe2/MoSe2 heterostructure using tip-enhanced photoluminescence (TEPL) with nanoscale spatial resolution and with picoscale tip-sample distance dependence. We demonstrate the observation of quantum plasmonic effects in 2D heterostructures on a non-metallic substrate, and we report the nano-optical measurements of the lateral 2D TMD heterojunction width of ~ 150 nm and the charge tunneling distance of ~ 20 pm. Controlling the plasmonic tip location allows for both nano-optical imaging and plasmon-induced hot electron injection into the heterostructure. By adjusting the tip-sample distance, we demonstrated the controllability of the hot-electron injection via the competition of two quantum plasmonic photoluminescence (PL) enhancement and quenching mechanisms. The directional charge transport in the depletion region leads to the increased hot electron injection, enhancing the MoSe2 PL signal. The properties of the directional hot-electron injection in the quantum plasmonic regime make the lateral 2D MoSe2/WSe2 heterostructures promising for quantum nanodevices with tunable photoresponse.

physics.optics↗

arXiv2016

Tip-enhanced Raman spectroscopic detection of aptamers

Single molecule detection, sequencing and conformational mapping of aptamers are important for improving medical and biosensing technologies and for better understanding of biological processes at the molecular level. We obtain vibrational signals of single aptamers immobilized on gold substrates using tip-enhanced Raman spectroscopy (TERS). We compare topographic and optical signals and investigate the fluctuations of the position-dependent TERS spectra. TERS mapping provides information about the chemical composition and conformation of aptamers, and paves the way to future single-molecule label-free sequencing.

q-bio.BM↗

arXiv2016

Network reconstruction by the stationary distribution of random walk process

It is known that the stationary distribution of the random walk process is dependent on the structure of the network. This could provide us a solution of the network reconstruction. However, the stationary distribution of the random walk process can only reflect the relative size of node degrees directly, how to infer the real connection is still a problem. In this paper, we will propose a method to reconstruct network by the random walk process, which can reconstruct the total number of links, degree sequence and links sequentially. In our method, only the stationary distribution is used, and no data of the evolution process is needed, such as the first passage time. We perform our method on some network models and real-world network, the results indicate our method can reconstruct networks accurately, even when we can not get the exact stationary distribution.

physics.soc-ph↗

arXiv2015

Bidirectional selection between two classes in complex social networks

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

physics.soc-ph↗

arXiv2015

A Model of Two-Way Selection System for Human Behavior

We propose a model of two-way selection system. It appears in the processes like choosing a mate between men and women, making contracts between job hunters and recruiters, and trading between buyers and sellers. In this paper, we propose a model of two-way selection system, and present its analytic solution for the expectation of successful matching total and the regular pattern that the matching rate trends toward an inverse proportion to either the ratio between the two sides or the ratio of the state total to the smaller people number. The proposed model is verified by empirical data of the matchmaking fairs. Results indicate that the model well predicts this typical real-world two- way selection behavior to the bounded error extent, thus it is helpful for understanding the dynamics mechanism of the real-world two-way selection system.

physics.gen-ph↗

arXiv2014

Network cluster detecting in associated bi-graph view

We find there is relationship between the associated bigraph and the cluster (or community) detecting on network. By imbedding the associated bigraph of some network (suppose it has cluster structures) into some space, we can identify the clusters on this network, which is a new method for network cluster detecting. And this method, of which the physical meaning is clear and the time complexity is acceptable, may provide us a new point to understand the structure and character of networks. In this paper, We test the methods on serval computer-generated networks and real networks. A computer-generated network with 128 vertexes and the Zachary Network, which presents the structure of a karate club, can be partitioned correctly by these methods. And the Dolphin Network, which presents the relationship between 62 dolphins on the coast of New Zealand, is partitioned reasonably.

physics.soc-ph↗

arXiv2014

The upper bound of packet transmission capacity in local static routings

We propose a universal analysis for static routings on networks and describe the congestion characteristics by the theory. The relation between average transmission time and transmission capacity is described by inequality T0Rc0<=1. For large scale sparse networks, the non-trivial upper bond of transmission capacity Rc0 is limited by Rc0<=1/< 1/k > in some approximate conditions. the theoretical results agree with simulations on BA Networks.

cs.NI↗