Zheng Wang

Zheng Wang
Hunan Normal University · School of Computer Science

Doctor of mathematics

About

21
Publications
3,234
Reads
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204
Citations
Citations since 2017
21 Research Items
204 Citations
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2017201820192020202120222023020406080
2017201820192020202120222023020406080

Publications

Publications (21)
Article
Full-text available
A diabetic foot ulcer(DFU) is a common chronic complication of diabetes because of the dysfunction of islets or receptors of insulin, and it has a high disability and mortality rate. Measuring diabetic foot ulcers is also one of the popular application areas where computer vision combines with deep learning techniques. However, some remaining defec...
Article
Full-text available
Objectives: Chronic suppurative otitis media (CSOM) and middle ear cholesteatoma (MEC) are the 2 most common chronic middle ear diseases. In the process of diagnosis and treatment, the 2 diseases are prone to misdiagnosis and missed diagnosis due to their similar clinical manifestations. High resolution computed tomography (HRCT) can clearly displ...
Article
Full-text available
Background Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, it may lead to lower limb amputation. At the initial stage, the detection of diabetes-related foot ulcer (DFU) is very difficult. Deep learning has demonstrated state-of-the-art performance in various fields and has been used to analyze images of DFUs...
Article
GPXs are a family of transcription factors encoded by a set of genes, which have been linked to tumor growth in a variety of cancers. GPXs are implicated in cutaneous melanoma carcinogenesis, according to growing experimental data. The expression patterns and prognostic values of eight GPXs were investigated in this study. The Oncomine, Gene Expres...
Article
Full-text available
Acne vulgaris, the most common skin disease, can cause substantial economic and psychological impacts to the people it affects, and its accurate grading plays a crucial role in the treatment of patients. In this paper, we firstly proposed an acne grading criterion that considers lesion classifications and a metric for producing accurate severity ra...
Preprint
Full-text available
Purpose: We aimed to develop endoplasmic reticulum (ER) stress-related risk signature to predict the prognosis of melanoma and elucidate the immune characteristics and benefit of immunotherapy in ER-related risk score-defined subgroups of melanoma based on a machine learning algorithm. Methods: Based on The Cancer Genome Atlas (TCGA) melanoma datas...
Article
Full-text available
Background and Aim: Esophageal cancer is the eighth most common cancer in the world. Currently, the incidence of esophageal cancer is increasing annually. Early detection of esophageal cancer can significantly improve the prognosis and quality of life of patients. However, detection of esophageal tumors remains a challenge because it depends on the...
Article
Full-text available
The main purpose of this paper was to develop a deep-learning method for the diagnosis of different chronic middle ear diseases, including middle ear cholesteatoma and chronic suppurative otitis media, based on computed tomography (CT) images of the middle ear. The origin of the dataset was the CT scans of 499 patients, which included both ears and...
Article
Full-text available
Cholangiocarcinoma (CCA) is featured by common occurrence and poor prognosis. Autophagy is a biological process that has been extensively involved in the progression of tumors. Long noncoding RNAs (lncRNAs) have been discovered to be critical in diagnosing and predicting various tumors. It may be valuable to elaborate autophagy-related lncRNAs (ARl...
Article
Purpose: Fully automated abdominal adipose tissue segmentation from computed tomography (CT) scans plays an important role in biomedical diagnoses and prognoses. However, to identify and segment subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in the abdominal region, the traditional routine process used in clinical practise is...
Article
In recent years, elliptic partial differential equations (PDEs) have been challenging in numerical mathematics, engineering, and physics. In this paper, we proposed a novel approach called Multilayer Neural Network for Partial Differential Equations (MLNPDE) based on deep learning algorithms by exploring the elliptic PDE family under certain condit...
Article
Diagnosis of the esophageal motility disorders is ongoing in clinical evaluations, which is based on traditional method called High-resolution manometry (HRM). However, the huge raw swallow data sets from the HRM are not allowed the doctors to interpret and classify the patients with esophageal symptoms. To this end, modeling propagation between vi...
Article
Full-text available
Solving high-dimensional partial differential equations (PDEs) is a long-term computational challenge due to the fundamental obstacle known as the curse of dimensionality. This paper develops a novel method (DL4HPDE) based on residual neural network learning with data-driven learning elliptic PDEs on a box-shaped domain. However, to combine a stron...
Article
Background and objective: Esophageal high-resolution manometry (HRM) is widely performed to evaluate the representation of manometric features in patients for diagnosing normal esophageal motility and motility disorders. Clinicians commonly assess esophageal motility function using a scheme termed the Chicago classification, which is difficult, ti...
Article
Full-text available
Jaundice occurs as a symptom of various diseases, such as hepatitis, the liver cancer, gallbladder or pancreas. Therefore, clinical measurement with special equipment is a common method that is used to identify the total serum bilirubin level in patients. Fully automated multi-class recognition of jaundice combines two key issues: (1) the critical...
Article
Full-text available
Accurate gold price prediction is highly essential for economic and currency markets. Thus, the intelligence prediction models need to be applied to price prediction. On the basis of long-term collected daily gold, the study proposes a novel genetic algorithm regularization online extreme learning machine (GA-ROSELM), to predict gold price data whi...
Article
The COVID-19 outbreak continues to threaten the health and life of people worldwide. It is an immediate priority to develop and test a computer-aided detection (CAD) scheme based on deep learning (DL) to automatically localize and differentiate COVID-19 from community-acquired pneumonia (CAP) on chest X-rays. Therefore, this study aims to develop a...
Article
Full-text available
One major role of an accurate distribution of abdominal adipose tissue is to predict disease risk. This paper proposes a novel effective three-level convolutional neural network (CNN) approach to automate the selection of abdominal computed tomography (CT) images on large-scale CT scans and automatically quantify the visceral and subcutaneous adipo...
Article
Full-text available
The traditional effective variance weighted least squares algorithms for solving CMB (Chemical Mass Balance) models have the following drawbacks: When there is collinearity among the sources or the number of species is less than the number of sources, then some negative value of contribution will appear in the results of the source apportionment or...
Conference Paper
Full-text available
Forecasting international iron ore is a well-known issue, BIC criterion is used to select the relevant variables of iron ore price. On the basis of the traditional extreme learning machine (ELM), the regular term is introduced to control the complexity of the model, and the genetic algorithm (GA) is used to regularize the extreme learning machine....
Article
In this paper, a robust consolidation method based on wavelets is presented for the defective polygonal mesh even polygon soup. The indicator function of a model is represented with wavelets, where the wavelet coefficients are computed by surface integrals over polygons. The hierarchical wavelet representation from defective inputs guarantees a con...

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Project (1)
Project
Medical image processing,GNN,deep learning. To achieve the combination of mathematics, artificial intelligence and medical.