Fusheng Wang

Fusheng Wang
Stony Brook University | Stony Brook · Department of Biomedical Informatics, Department of Computer Science

Ph.D.

About

279
Publications
62,890
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4,829
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Introduction
My research covers Spatial Big Data Management, GIS, Medical Imaging Informatics, AI in Healthcare, Population Health and Opioid Epidemic Research.
Additional affiliations
January 2018 - present
Stony Brook University
Position
  • Professor (Associate)
January 2015 - December 2017
Stony Brook University
Position
  • Professor (Assistant)
December 2011 - January 2015
Emory University
Position
  • Professor (Assistant)

Publications

Publications (279)
Article
Objective: In the era of precision medicine, human tumor atlas-oriented studies have been significantly facilitated by high-resolution, multi-modal tissue based microscopic pathology image analytics. To better support such tissue-based investigations, we have developed Digital Pathology Laboratory (DPLab), a publicly available web-based platform,...
Preprint
Full-text available
Liver fibrosis staging is clinically important for liver disease progression prediction. As the portal tract fibrotic quantity and size in a liver biopsy correlate with the fibrosis stage, an accurate analysis of portal tract regions is clinically critical. Manual annotations of portal tract regions, however, are time-consuming and subject to large...
Article
Liver fibrosis staging is clinically important for liver disease progression prediction. As the portal tract fibrotic quantity and size in a liver biopsy correlate with the fibrosis stage, an accurate analysis of portal tract regions is clinically critical. Manual annotations of portal tract regions, however, are time-consuming and subject to large...
Article
Motivation Predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients accurately is direly needed for clinical decision making. pCR is also regarded as a strong predictor of overall survival. In this work, we propose a deep learning system to predict pCR to NAC based on serial...
Preprint
Deep-learning-based clinical decision support using structured electronic health records (EHR) has been an active research area for predicting risks of mortality and diseases. Meanwhile, large amounts of narrative clinical notes provide complementary information, but are often not integrated into predictive models. In this paper, we provide a novel...
Article
3D spatial data has been generated at an extreme scale from many emerging applications, such as high definition maps for autonomous driving and 3D Human BioMolecular Atlas. In particular, 3D digital pathology provides a revolutionary approach to map human tissues in 3D, which is highly promising for advancing computer-aided diagnosis and understand...
Preprint
In the era of precision medicine, human tumor atlas oriented studies have been significantly facilitated by high-resolution, multi-modal tissue based microscopic pathology image analytics. To better support such tissue based investigations, we develop Digital Pathology Laboratory (DPLab), a publicly available web-based platform, to assist biomedica...
Preprint
Introduction Prevalently considered as the “gold-standard” for diagnosis of hepatic fibrosis and cirrhosis, the clinical liver needle biopsy is known to be subject to inadequate sampling and a high mis-sampling rate. However, quantifying such sampling bias has been difficult as generating a large number of needle biopsies from the same living patie...
Preprint
Whole-slide image (WSI) analysis has been largely performed in a 2D tissue space to support routine pathology diagnosis and imaging based biomedical research. For a more definitive representation and characterization of the tissue spatial space, it is critical to extend such tissue based investigations to a 3D space by spatially aligning 2D serial...
Article
Full-text available
Background Oncotype DX Recurrence Score (RS) has been widely used to predict chemotherapy benefits in patients with estrogen receptor-positive breast cancer. Studies showed that the features used in Magee equations correlate with RS. We aimed to examine whether deep learning (DL)-based histology image analyses can enhance such correlations.Methods...
Article
Full-text available
Introduction: Prevalently considered as the "gold-standard" for diagnosis of hepatic fibrosis and cirrhosis, the clinical liver needle biopsy is known to be subject to inadequate sampling and a high mis-sampling rate. However, quantifying such sampling bias has been difficult as generating a large number of needle biopsies from the same living pat...
Preprint
Predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients accurately is direly needed for clinical decision making. pCR is also regarded as a strong predictor of overall survival. In this work, we propose a deep learning system to predict pCR to NAC based on serial pathology i...
Article
Background Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE aging is accompanied by changes in cell morphological features, an accurate segmentation of RPE cells is a prerequisite to such morphology analyses. Due the overwhelmingly large cell number, manual annotations of RPE cell borders are time-consuming. Compu...
Article
Full-text available
Background Opioid addiction and overdose have a large burden of disease and mortality in New York State (NYS). The medication naloxone can reverse an overdose, and buprenorphine can treat opioid use disorder. Efforts to increase the accessibility of both medications include a naloxone standing order and a waiver program for prescribing buprenorphin...
Conference Paper
Full-text available
Large-scale three-dimensional spatial data has gained increasing attention with the development of self-driving, mineral exploration , CAD, and human atlases. Such 3D objects are often represented with a polygonal model at high resolution to preserve accuracy. This poses major challenges for 3D data management and spatial queries due to the massive...
Preprint
Background Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE aging is accompanied by changes in cell morphological features, an accurate segmentation of RPE cells is a prerequisite to such morphology analyses. Due the overwhelmingly large cell number, manual annotations of RPE cell borders are time-consuming. Compu...
Conference Paper
Full-text available
Selecting targets accurately and quickly with eye-gaze input remains an open research question. In this paper, we introduce BayesGaze, a Bayesian approach of determining the selected target given an eye-gaze trajectory. This approach views each sampling point in an eye-gaze trajectory as a signal for selecting a target. It then uses the Bayes' theo...
Article
Artificial intelligence (AI) has been transforming the practice of drug discovery in the past decade. Various AI techniques have been used in many drug discovery applications, such as virtual screening and drug design. In this survey, we first give an overview on drug discovery and discuss related applications, which can be reduced to two major tas...
Conference Paper
Contact tracing is gaining its importance in controlling the spread of COVID-19. However, the enormous volume of the frequently sampled tracing data brings major challenges for real-time processing. In this paper, we propose a GPU-based real-time contact tracing system based on spatial proximity queries with temporal constraints using location data...
Chapter
Full-text available
In triple negative breast cancer (TNBC) treatment, early prediction of pathological complete response (PCR) from chemotherapy before surgical operations is crucial for optimal treatment planning. We propose a novel deep learning-based system to predict PCR to neoadjuvant chemotherapy for TNBC patients with multi-stained histopathology images of ser...
Preprint
BACKGROUND Opioid addiction and overdose have a large burden of disease and mortality in New York State (NYS). The medication naloxone can reverse an overdose, and buprenorphine can treat opioid use disorder. Efforts to increase the accessibility of both medications include a naloxone standing order and a waiver program for prescribing buprenorphin...
Preprint
Full-text available
Artificial intelligence (AI) has been transforming the practice of drug discovery in the past decade. Various AI techniques have been used in many drug discovery applications, such as virtual screening and drug design. In this survey, we first give an overview on drug discovery and discuss related applications, which can be reduced to two major tas...
Article
Motivation: In most tissue-based biomedical research, the lack of sufficient pathology training images with well-annotated ground truth inevitably limits the performance of deep learning systems. In this study, we propose a convolutional neural network with foveal blur enriching datasets with multiple local nuclei regions of interest derived from...
Article
Full-text available
Background The USA is in the midst of an opioid overdose epidemic. To address the epidemic, we conducted a large-scale population study on opioid overdose.Objectives The primary objective of this study was to evaluate the temporal trends and risk factors of inpatient opioid overdose. Based on its patterns, the secondary objective was to examine the...
Article
Selecting targets accurately and quickly with eye-gaze input remains an open research question. In this paper, we introduce BayesGaze, a Bayesian approach of determining the selected target given an eye-gaze trajectory. This approach views each sampling point in an eye-gaze trajectory as a signal for selecting a target. It then uses the Bayes' theo...
Article
Full-text available
Objective: The United States is experiencing an opioid epidemic. In recent years, there were more than 10 million opioid misusers aged 12 years or older annually. Identifying patients at high risk of opioid use disorder (OUD) can help to make early clinical interventions to reduce the risk of OUD. Our goal is to develop and evaluate models to pred...
Conference Paper
In this paper, we propose a method that optimizes a regularization parameter for the regularized Free Form Deformation (FFD) non-rigid image registration. The developed process utilizes autoencoder generated image representations to assess image data generalization quality by the regularization parameter. Both pixel intensity and learned features a...
Conference Paper
Three-dimensional (3D) digital pathology has been emerging for next-generation tissue based cancer research. To enable such histopathology image volume analysis, serial histopathology slides need to be well aligned. In this paper, we propose a histopathology image registration fine tuning method with integrated landmark evaluations by texture and s...
Article
Purpose: Retinal pigment epithelial (RPE) cells serve as a supporter for the metabolism and visual function of photoreceptors and a barrier for photoreceptor protection. Morphology dynamics, spatial organization, distribution density, and growth patterns of RPE cells are important for further research on these RPE main functions. To enable such in...
Conference Paper
With the advent of IoT and emerging 5G technology, real-time streaming data are being generated at unprecedented speed and volume, and coming with both temporal and spatial dimensions. Effective analysis at such scale and speed requires support for dynamically adjusting querying capabilities in real-time. In spatio-temporal domain, this warrants fo...
Article
Full-text available
Opioid overdose related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP). To discover trends and patterns of opioid poisoning and the demographic and regional disparities, we analyzed large scale patient visits data in New York State (NYS). D...
Article
Full-text available
The US is experiencing an opioid epidemic, such that opioid overdose is causing more than 100 deaths per day. Identifying patients at high risk of Opioid Overdose (OD) can help to make early clinical interventions to reduce the risk of OD. We aim to build a deep learning model that can predict the patients at high risk for opioid overdose and ident...
Article
This report describes the development and finalization of the 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2020), held virtually online, November 3-6, 2020. The attendance for the 2020 conference was 999, the highest in the history of ACM SIGSPATIAL.
Article
Full-text available
Liver cancer is one of the leading causes of cancer deaths in Asia and Africa. It is caused by the Hepatocellular carcinoma (HCC) in almost 90% of all cases. HCC is a malignant tumor and the most common histological type of the primary liver cancers. The detection and evaluation of viable tumor regions in HCC present an important clinical significa...
Book
This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and the 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2020, which were held virtually on...
Chapter
Synthetic electronic health records (EHR) can facilitate effective use of clinical data in software development, medical education, and medical research without the concerns of data privacy. We propose a novel Generative Adversarial Network (GAN) approach, called Longitudinal GAN (LongGAN), that can generate synthetic longitudinal EHR data. LongGAN...
Book
This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2021, and the 7th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2021, which were held virtually on...
Article
Full-text available
Background Diabetes affects more than 30 million patients across the United States. With such a large disease burden, even a small error in classification can be significant. Currently billing codes, assigned at the time of a medical encounter, are the “gold standard” reflecting the actual diseases present in an individual, and thus in aggregate re...
Preprint
Full-text available
Chronic kidney disease (CKD) has a poor prognosis due to excessive risk factors and comorbidities associated with it. The early detection of CKD faces challenges of insufficient medical histories of positive patients and complicated risk factors. In this paper, we propose the TRACE (Transformer-RNN Autoencoder-enhanced CKD Detector) framework, an e...
Conference Paper
Full-text available
Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This depends on critical knowledge to understand the risk of opioid overdose of patients. In this paper, w...
Preprint
Full-text available
Background The United States is in the midst of an opioid overdose epidemic. We evaluated the temporal trends and risk factors of inpatient opioid overdose. Based on the opioid overdose patterns, we further examined the innate properties underlying less overdose events. Methods We conducted a retrospective cross-sectional study based a large-scale...
Preprint
Full-text available
The SPIDAL (Scalable Parallel Interoperable Data Analytics Library) project was begun in Fall 2014 and has reached a technical completion in Fall 2020 with outreach activities continuing in 2021. The February Poster summarizes the 2020 status and activity very well with previous work through September 2018 summarized in a book chapter with extensiv...
Preprint
Full-text available
The United States is experiencing an opioid epidemic, and there were more than 10 million opioid misusers aged 12 or older each year. Identifying patients at high risk of Opioid Use Disorder (OUD) can help to make early clinical interventions to reduce the risk of OUD. Our goal is to predict OUD patients among opioid prescription users through anal...
Chapter
Full-text available
Neoadjuvant chemotherapy is widely used to reduce tumor size to make surgical excision manageable and to minimize distant metastasis. Assessing and accurately predicting pathological complete response is important in treatment planing for breast cancer patients. In this study, we propose a novel approach integrating 3D MRI imaging data, molecular d...
Preprint
Full-text available
Background: Opioid overdose related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD). Objective: We aimed to discover geospatial patterns in problematic opioid use and its correlations with demographic features r...
Preprint
Full-text available
Introduction: To discover trends and patterns of opioid poisoning and the demographic and regional disparities by analyzing large scale patient visits data in New York State (NYS). Methods: Demographic, spatial, temporal and correlation analyses were performed for all OP patients extracted from the New York Statewide Planning and Research Cooperati...
Article
Background Opioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD). Objective We aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features rela...
Preprint
BACKGROUND Opioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD). OBJECTIVE We aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features rel...
Conference Paper
Generative adversarial networks (GANs) have been highly successful for generating realistic synthetic data. In healthcare, synthetic data generation can be helpful for producing annotated data and improving data-driven research without worries on data privacy. However, electronic health records (EHRs) are noisy, incomplete and complex, and existing...
Preprint
BACKGROUND Diabetes affects more than 30 million patients across the United States. With such a large disease burden, even a small error in classification can be significant. Currently billing codes, assigned at the time of a medical encounter, are the “gold standard” reflecting the actual diseases present in an individual, and thus in aggregate re...
Article
Hepatic steatosis droplet quantification with histology biopsies has high clinical significance for risk stratification and management of patients with fatty liver diseases and in the decision to use donor livers for transplantation. However, pathology reviewing processes, when conducted manually, are subject to a high inter- and intra-reader varia...
Article
Full-text available
Drug-drug interactions (DDI) can cause severe adverse drug reactions and pose a major challenge to medication therapy. Recently, informatics-based approaches are emerging for DDI studies. In this paper, we aim to identify key pharmacological components in DDI based on large-scale data from DrugBank, a comprehensive DDI database. With pharmacologica...
Article
Full-text available
Spatial cross-matching operation over geospatial polygonal datasets is a highly compute-intensive yet an essential task to a wide array of real-world applications. At the same time, modern computing systems are typically equipped with multiple processing units capable of task parallelization and optimization at various levels. This mandates for the...
Conference Paper
3D organ contouring is an essential step in radiation therapy treatment planning for organ dose estimation as well as for optimizing plans to reduce organs-at-risk doses. Manual contouring is time-consuming and its inter-clinician variability adversely affects the outcomes study. Such organs also vary dramatically on sizes - up to two orders of mag...
Preprint
Full-text available
Naloxone, an opioid antagonist, has been widely used to save lives from opioid overdose, a leading cause for death in the opioid epidemic. However, naloxone has short brain retention ability, which limits its therapeutic efficacy. Developing better opioid antagonists is critical in combating the opioid epidemic.Instead of exhaustively searching in...
Article
Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This depends on critical knowledge to understand the risk of opioid overdose of patients. In this paper, w...
Article
Full-text available
Heart failure (HF) is among the most costly diseases to our society, and the prevalence keeps on increasing these days. Early detection of HF plays a vital role in saving lives through adjusting lifestyles and drug interventions that can slow down disease progression or prevent HF. There are many cardiovascular risk factors associated with HF, and...
Preprint
Full-text available
Drug-drug interactions (DDI) can cause severe adverse drug reactions and pose a major challenge to medication therapy. Recently, informatics-based approaches are emerging for DDI studies. In this paper, we aim to identify key pharmacological components in DDI based on large-scale data from DrugBank, a comprehensive DDI database. With pharmacologica...