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Articles 178411 - 178440 of 1738367
Full-Text Articles in Entire DC Network
Reward Penalties On Augmented States For Solving Richly Constrained Rl Effectively, Jiang Hao, Tien Mai, Pradeep Varakanthan, Minh Huy Hoang
Reward Penalties On Augmented States For Solving Richly Constrained Rl Effectively, Jiang Hao, Tien Mai, Pradeep Varakanthan, Minh Huy Hoang
Research Collection School Of Computing and Information Systems
Constrained Reinforcement Learning employs trajectory-based cost constraints (such as expected cost, Value at Risk, or Conditional VaR cost) to compute safe policies. The challenge lies in handling these constraints effectively while optimizing expected reward. Existing methods convert such trajectory-based constraints into local cost constraints, but they rely on cost estimates, leading to either aggressive or conservative solutions with regards to cost. We propose an unconstrained formulation that employs reward penalties over states augmented with costs to compute safe policies. Unlike standard primal-dual methods, our approach penalizes only infeasible trajectories through state augmentation. This ensures that increasing the penalty parameter always …
Decentralized Multimedia Data Sharing In Iov: A Learning-Based Equilibrium Of Supply And Demand, Jiani Fan, Minrui Xu, Jiale Guo, Lwin Khin Shar, Jiawen Kang, Dusit Niyato, Kwok-Yan Lam
Decentralized Multimedia Data Sharing In Iov: A Learning-Based Equilibrium Of Supply And Demand, Jiani Fan, Minrui Xu, Jiale Guo, Lwin Khin Shar, Jiawen Kang, Dusit Niyato, Kwok-Yan Lam
Research Collection School Of Computing and Information Systems
The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. However, decentralized data sharing may not achieve the expected efficiency if there are IoV users who only want to consume the shared data but are not willing to contribute their own data to the community, resulting in incomplete information observed by other vehicles and infrastructure, which can introduce additional transmission latency. Therefore, in this paper, by modeling the …
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Research Collection School Of Computing and Information Systems
Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …
Stopguess: A Framework For Public-Key Authenticated Encryption With Keyword Search, Tao Xiang, Zhongming Wang, Biwen Chen, Xiaoguo Li, Peng Wang, Fei Chen
Stopguess: A Framework For Public-Key Authenticated Encryption With Keyword Search, Tao Xiang, Zhongming Wang, Biwen Chen, Xiaoguo Li, Peng Wang, Fei Chen
Research Collection School Of Computing and Information Systems
Public key encryption with keyword search (PEKS) allows users to search on encrypted data without leaking the keyword information from the ciphertexts. But it does not preserve keyword privacy within the trapdoors, because an adversary (e.g., untrusted server) might launch inside keyword-guessing attacks (IKGA) to guess keywords from the trapdoors. In recent years, public key authenticated encryption with keyword search (PAEKS) has become a promising primitive to counter the IKGA. However, existing PAEKS schemes focus on the concrete construction of PAEKS, making them unable to support modular construction, intuitive proof, or flexible extension. In this paper, our proposal called “StopGuess” …
Multiobjective Stochastic Optimization: A Case Of Real-Time Matching In Ride-Sourcing Markets, Guodong Lyu, Wang Chi Cheung, Chung-Piaw Teo, Hai Wang
Multiobjective Stochastic Optimization: A Case Of Real-Time Matching In Ride-Sourcing Markets, Guodong Lyu, Wang Chi Cheung, Chung-Piaw Teo, Hai Wang
Research Collection School Of Computing and Information Systems
Problem Definition: The job of any marketplace is to facilitate the matching of supply with demand in real-time. Success is often measured using various metrics. The challenge is to design matching algorithms to balance the trade-offs among multiple objectives in a stochastic environment, to arrive at a “compromise” solution, which minimizes say the ℓp-norm-based distance function (for some 1 ≤p ≤∞) between the attained performance metrics and the target performances.Methodology/Results: We observe that the sample-average-approximation formulation of this multi-objective stochastic optimization problem can be solved by an online algorithm that uses only gradient information from “historical” (i.e., past) sample information, …
Ddos Family: A Novel Perspective For Massive Types Of Ddos Attacks, Ziming Zhao, Zhaoxuan Li, Zhihao Zhou, Jiongchi Yu, Zhuoxue Song, Xiaofei Xie, Fan Zhang, Rui Zhang
Ddos Family: A Novel Perspective For Massive Types Of Ddos Attacks, Ziming Zhao, Zhaoxuan Li, Zhihao Zhou, Jiongchi Yu, Zhuoxue Song, Xiaofei Xie, Fan Zhang, Rui Zhang
Research Collection School Of Computing and Information Systems
Distributed Denial of Service (DDoS) defense is a profound research problem. In recent years, adversaries tend to complicate their attack strategies by crafting vast DDoS variants. On the one hand, this trend exacerbates both extremes of classification granularity (i.e., binary and attack level) in existing machine learning methods. On the other hand, massive attack categories make the filter rule table bulky, as well as cause problems of slow reaction presented in the recent state-of-the-art DDoS mitigation system. Therefore, we propose the concept of a DDoS family to reconcile/cope with these issues. The specific technical roadmap includes traffic pattern characterization, attack …
From Asset Flow To Status, Action And Intention Discovery: Early Malice Detection In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu
From Asset Flow To Status, Action And Intention Discovery: Early Malice Detection In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu
Research Collection School Of Computing and Information Systems
Cryptocurrency has been subject to illicit activities probably more often than traditional financial assets due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all three critical properties of early detection, good interpretability, and versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without interpretability and are only available for retrospective analysis of a specific illicit type. To tackle all these challenges, we propose Intention Monitor for early malice detection in Bitcoin, where the on-chain record data for a certain …
Understanding Newcomers' Onboarding Process In Deep Learning Projects, Junxiao Han, Jiahao Zhang, David Lo, Xin Xia, Shuigang Deng, Minghui Wu
Understanding Newcomers' Onboarding Process In Deep Learning Projects, Junxiao Han, Jiahao Zhang, David Lo, Xin Xia, Shuigang Deng, Minghui Wu
Research Collection School Of Computing and Information Systems
Attracting and retaining newcomers are critical for the sustainable development of Open Source Software (OSS) projects. Considerable efforts have been made to help newcomers identify and overcome barriers in the onboarding process. However, fewer studies focus on newcomers’ activities before their successful onboarding. Given the rising popularity of deep learning (DL) techniques, we wonder what the onboarding process of DL newcomers is, and if there exist commonalities or differences in the onboarding process for DL and non-DL newcomers. Therefore, we reported a study to understand the growth trends of DL and non-DL newcomers, mine DL and non-DL newcomers’ activities before …
Temporal Implicit Multimodal Networks For Investment And Risk Management, Meng Kiat Gary Ang, Ee-Peng Lim
Temporal Implicit Multimodal Networks For Investment And Risk Management, Meng Kiat Gary Ang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Many deep learning works on financial time-series forecasting focus on predicting future prices/returns of individual assets with numerical price-related information for trading, and hence propose models designed for univariate, single-task, and/or unimodal settings. Forecasting for investment and risk management involves multiple tasks in multivariate settings: forecasts of expected returns and risks of assets in portfolios, and correlations between these assets. As different sources/types of time-series influence future returns, risks, and correlations of assets in different ways, it is also important to capture time-series from different modalities. Hence, this article addresses financial time-series forecasting for investment and risk management in a …
Needs Assessment For Breast Health Education At Lvhn: A Qualitative Survey Of Primary Care And Obgyn Clinicians, Taylor Guth Md, Beth Careyva M.D.
Needs Assessment For Breast Health Education At Lvhn: A Qualitative Survey Of Primary Care And Obgyn Clinicians, Taylor Guth Md, Beth Careyva M.D.
USF-LVHN SELECT
No abstract provided.
A Survey Analysis On Family Leave Policies And Experiences Among Medical Trainees And Attending Physicians, Kristina Rozova Md, Shanika Esparaz, Meghana Chalasani, Michelle Tran, Anuk Burli
A Survey Analysis On Family Leave Policies And Experiences Among Medical Trainees And Attending Physicians, Kristina Rozova Md, Shanika Esparaz, Meghana Chalasani, Michelle Tran, Anuk Burli
USF-LVHN SELECT
No abstract provided.
Impacting Cervical Cancer Disparities In Hispanic Women In The Lehigh Valley, Melissa Sur Md, Autumn Kieber-Emmons Md, Mph
Impacting Cervical Cancer Disparities In Hispanic Women In The Lehigh Valley, Melissa Sur Md, Autumn Kieber-Emmons Md, Mph
USF-LVHN SELECT
No abstract provided.
Excellent Outcomes Of Atypical Fibroxanthoma Warrant Specific Diagnosis, Erin Mcclure Md, Michael Carr, Ayushi Y. Patel Md, Syed Mahrukh Hussnain Naqvi, Youngchul Kim, Michael Harrington, Wayne Cruse, Ricardo J. Gonzalez, Vernon Sondak, Amod Sarnaik, Jane Messina, Jonathan Zager
Excellent Outcomes Of Atypical Fibroxanthoma Warrant Specific Diagnosis, Erin Mcclure Md, Michael Carr, Ayushi Y. Patel Md, Syed Mahrukh Hussnain Naqvi, Youngchul Kim, Michael Harrington, Wayne Cruse, Ricardo J. Gonzalez, Vernon Sondak, Amod Sarnaik, Jane Messina, Jonathan Zager
USF-LVHN SELECT
No abstract provided.
Select Anesthesiology Interest Group Needs Assessment And Quality Improvement, Brett O'Donnell Md, Thomas A. Mcloughlin Md
Select Anesthesiology Interest Group Needs Assessment And Quality Improvement, Brett O'Donnell Md, Thomas A. Mcloughlin Md
USF-LVHN SELECT
No abstract provided.
Implementation Of A Prediabetes Decision Aid In Primary Care, Lindsay Kim Md, Beth Careyva M.D., Autumn Kieber-Emmons Md, Mph, Nicole M. Burgess Bs, Roya Hamadani Mph, Aashka Patel
Implementation Of A Prediabetes Decision Aid In Primary Care, Lindsay Kim Md, Beth Careyva M.D., Autumn Kieber-Emmons Md, Mph, Nicole M. Burgess Bs, Roya Hamadani Mph, Aashka Patel
USF-LVHN SELECT
No abstract provided.
Attack As Detection: Using Adversarial Attack Methods To Detect Abnormal Examples, Zhe Zhao, Guangke Chen, Tong Liu, Taishan Li, Fu Song, Jingyi Wang, Jun Sun
Attack As Detection: Using Adversarial Attack Methods To Detect Abnormal Examples, Zhe Zhao, Guangke Chen, Tong Liu, Taishan Li, Fu Song, Jingyi Wang, Jun Sun
Research Collection School Of Computing and Information Systems
As a new programming paradigm, deep learning (DL) has achieved impressive performance in areas such as image processing and speech recognition, and has expanded its application to solve many real-world problems. However, neural networks and DL are normally black-box systems; even worse, DL-based software are vulnerable to threats from abnormal examples, such as adversarial and backdoored examples constructed by attackers with malicious intentions as well as unintentionally mislabeled samples. Therefore, it is important and urgent to detect such abnormal examples. Although various detection approaches have been proposed respectively addressing some specific types of abnormal examples, they suffer from some limitations; …
Xfuzz: Machine Learning Guided Cross-Contract Fuzzing, Yinxing Xue, Jiaming Ye, Wei Zhang, Jun Sun, Lei Ma, Haijun Wang, Jianjun Zhao
Xfuzz: Machine Learning Guided Cross-Contract Fuzzing, Yinxing Xue, Jiaming Ye, Wei Zhang, Jun Sun, Lei Ma, Haijun Wang, Jianjun Zhao
Research Collection School Of Computing and Information Systems
Smart contract transactions are increasingly interleaved by cross-contract calls. While many tools have been developed to identify a common set of vulnerabilities, the cross-contract vulnerability is overlooked by existing tools. Cross-contract vulnerabilities are exploitable bugs that manifest in the presence of more than two interacting contracts. Existing methods are however limited to analyze a maximum of two contracts at the same time. Detecting cross-contract vulnerabilities is highly non-trivial. With multiple interacting contracts, the search space is much larger than that of a single contract. To address this problem, we present xFuzz , a machine learning guided smart contract fuzzing framework. …
Representation Learning For Stack Overflow Posts: How Far Are We?, Junda He, Xin Zhou, Bowen Xu, Ting Zhang, Kisub Kim, Zhou Yang, Thung Ferdian, Ivana Clairine Irsan, David Lo
Representation Learning For Stack Overflow Posts: How Far Are We?, Junda He, Xin Zhou, Bowen Xu, Ting Zhang, Kisub Kim, Zhou Yang, Thung Ferdian, Ivana Clairine Irsan, David Lo
Research Collection School Of Computing and Information Systems
The tremendous success of Stack Overflow has accumulated an extensive corpus of software engineering knowledge, thus motivating researchers to propose various solutions for analyzing its content. The performance of such solutions hinges significantly on the selection of representation models for Stack Overflow posts. As the volume of literature on Stack Overflow continues to burgeon, it highlights the need for a powerful Stack Overflow post representation model and drives researchers’ interest in developing specialized representation models that can adeptly capture the intricacies of Stack Overflow posts. The state-of-the-art (SOTA) Stack Overflow post representation models are Post2Vec and BERTOverflow, which are built …
Image Of Women In Islam: Maqāsid Approach For Correct Interpretation, Maher Haswa, Man Baker, Moath Alnaief
Image Of Women In Islam: Maqāsid Approach For Correct Interpretation, Maher Haswa, Man Baker, Moath Alnaief
All Works
The current study attempted to outline the necessity of using the purposes method (al-manhaj al-maqāṣidi) to understand the correct meaning of Islamic religious texts, particularly those related to the image of women, by analysing a set of Prophetic Hadiths in the canonical works of al-Bukhari and Muslim. When the purposes method is not utilized, these texts are typically understood as hostile towards women, leading many to question their validity. The current study employed the analytical and critical methods derived from holistically viewing the religious texts. The study argued that the purposes method should be used by gathering all the texts …
Dispositional Gratitude At Work Predicts Job Satisfaction Of Software Developers, Jordan Gabriel Tate
Dispositional Gratitude At Work Predicts Job Satisfaction Of Software Developers, Jordan Gabriel Tate
Electronic Theses and Dissertations
Software developers can suffer from negative emotions at work and low job satisfaction. Less is known about how positive emotions at work impact software developers. Gratitude is one positive emotion that has predicted job satisfaction in other studies. The purpose of this quantitative correlational study was to explore how gratitude at work predicts job satisfaction among software developers. The broaden-and-build theory of positive emotions and the find-remind-and-bind theory of gratitude guided the study. Participants included 146 software developers who were recruited via LinkedIn using purposive sampling. Participants completed an online survey, including the Gratitude Questionnaire-Six Item Form and the Appreciation …
Powerful Radio Sources In The Southern Sky. Iii. First Results Of The Optical Spectroscopic Campaign, A. García-Pérez, H. A. Peña-Herazo, A. Jimenez-Gallardo, V. Chavushyan, F. Massaro, S. V. White, A. Capetti, B. Balmaverde, W. R. Forman, Juan P. Madrid
Powerful Radio Sources In The Southern Sky. Iii. First Results Of The Optical Spectroscopic Campaign, A. García-Pérez, H. A. Peña-Herazo, A. Jimenez-Gallardo, V. Chavushyan, F. Massaro, S. V. White, A. Capetti, B. Balmaverde, W. R. Forman, Juan P. Madrid
Physics & Astronomy Faculty Publications
We recently built the G4Jy-3CRE catalog of extragalactic radio sources. This catalog lists 264 powerful radio sources selected with similar criteria to those of the revised Third Cambridge Catalog, but visible from the Southern Hemisphere. A literature search revealed that 119 sources in the G4Jy-3CRE catalog (i.e., 45%) lack a firm spectroscopic redshift measurement. Here, we present a campaign aimed at acquiring optical spectra of G4Jy-3CRE sources and measuring their redshifts. We used single-slit observations obtained with the Víctor Blanco Telescope, the New Technology Telescope, the Southern Astrophysical Research Telescope, and the 2.1 m telescope of the Observatorio Astronómico Nacional …
Comment On “Spectral Shifts In General Relativity,” [Am. J. Phys. 62(10), 903–907 (1994)], Joseph D. Romano, Teviet Creighton
Comment On “Spectral Shifts In General Relativity,” [Am. J. Phys. 62(10), 903–907 (1994)], Joseph D. Romano, Teviet Creighton
Physics & Astronomy Faculty Publications
No abstract provided.
“Safe” Annuity Retirement Products And A Possible Us Retirement Crisis, Thomas E. Lambert, Christopher B. Tobe
“Safe” Annuity Retirement Products And A Possible Us Retirement Crisis, Thomas E. Lambert, Christopher B. Tobe
Faculty and Staff Scholarship
This paper examines a looming possible crisis in many Americans’ retirement plans due to the proliferation of annuity products in their retirement investment portfolios. As defined benefit pension plans have almost completely disappeared as a means of retirement savings and have been replaced by defined contribution retirement plans over the last 40 to 50 years, a great number of private and public sector defined contribution retirement plans have become laden with insurance contracts called annuities. Of the remaining solid defined benefit plans many, through a process called Pension Risk Transfer are being converted to high-risk single entity annuities. Such products …
Improving Inpatient Hyperglycaemia In Non-Critically Ill Adults In Resident Wards Through Audit And Feedback, Chelsea H. Chang, Alcibiades Fleires, Alfarooq Alshaikhli, Hector Arredondo, Diana Gavilanes, Francisco J. Cabral-Amador, Jonathon Cantu, Daniela Bazan, Kathryn Oliveira Oliveira, Rene Verduzco, Lina Pedraza Sanchez
Improving Inpatient Hyperglycaemia In Non-Critically Ill Adults In Resident Wards Through Audit And Feedback, Chelsea H. Chang, Alcibiades Fleires, Alfarooq Alshaikhli, Hector Arredondo, Diana Gavilanes, Francisco J. Cabral-Amador, Jonathon Cantu, Daniela Bazan, Kathryn Oliveira Oliveira, Rene Verduzco, Lina Pedraza Sanchez
School of Medicine Publications
Inpatient hyperglycaemia is associated with an increase in morbidity and mortality, number of rehospitalisations and length of hospitalisation. Although the advantages of proper glycaemic control in hospitalised patients with diabetes are well established, a variety of barriers limit accomplishment of blood glucose targets. Our primary aim was to decrease the number of glucose values above 180 mg/dL in non-critical care hospitalised patients using an audit and feedback intervention with pharmacy and internal medicine residents. A resident-led multidisciplinary team implemented the quality improvement (QI) project including conception, literature review, educating residents, iterative development of audit and feedback tools and data analysis. …
Identification Of Quantitative Trait Loci (Qtl) For Sucrose And Protein Content In Soybean Seed, Daniel R. Jamison, Pengyin Chen, Navam Hettiarachchy, David M. Miller, Ehsanollah Shakiba
Identification Of Quantitative Trait Loci (Qtl) For Sucrose And Protein Content In Soybean Seed, Daniel R. Jamison, Pengyin Chen, Navam Hettiarachchy, David M. Miller, Ehsanollah Shakiba
Food Science Faculty Publications and Presentations
Protein and sugar content are important seed quality traits in soybean because they improve the value and sustainability of soy food and feed products. Thus, identifying Quantitative Trait Loci (QTL) for soybean seed protein and sugar content can benefit plant breeders and the soybean market by accelerating the breeding process via marker-assisted selection. For this study, a population of recombinant inbred lines (RILs) was developed from a cross between R08-3221 (high protein and low sucrose) and R07-2000 (high sucrose and low protein). Phenotypic data for protein content were taken from the F2:4 and F2:5 generations. The DA7250 NIR analyzer and …
A Phenomenological Study Of School Psychologists: The Influence Of Implicit Bias On The Disproportionate Identification Rates Of African American Students Evaluated For Emotional Disturbance, Sonya Coe-Milo
Electronic Theses and Dissertations
As advocates, school psychologists remain ethically responsible and uniquely positioned to identify social injustices and promote nondiscriminatory practices in prekindergarten through grade 12 public education institutions. Implicit bias and its influence on African American students is one such practice. In public education, implicit bias contributes to discipline disproportionality, differentiated teacher support, pedagogical practices, and adult perceptions and expectations of appropriate and inappropriate behaviors. These factors directly correlate to the disproportionate identification rates of African American students for special education and related services. Therefore, this phenomenological qualitative study examined the personal, lived experiences and perceptions of school psychologists regarding implicit bias …
Community-Engaged Pedagogy For Equitable Hsi Teacher Preparation: Bridging Community, School, And University Cultures, Pauli Badenhorst, Sandra I. Musanti, Veronica L. Estrada, Patricia Robles, Amy Montoya
Community-Engaged Pedagogy For Equitable Hsi Teacher Preparation: Bridging Community, School, And University Cultures, Pauli Badenhorst, Sandra I. Musanti, Veronica L. Estrada, Patricia Robles, Amy Montoya
Teaching and Learning Faculty Publications
Drawing on interview data collected as part of a qualitative study among thirty-two local educators and community advocates in the borderlands context of the Lower Rio Grande Valley (RGV), we inquire about the fundamental characteristics of being a community-engaged teacher for sustainable and equitable Latinx student teaching and learning. The ultimate purpose is to collectively develop a model of community-engaged pedagogy that will bridge school and university cultures. Based on our findings, a community-engaged teacher preparation approach should prioritize that teacher candidates can establish rapport and relationship with students and their families; grapple with the contradictions entrenched in a prevalent …
Meeting Report On The 3rd Chinese American Society For Mass Spectrometry Conference-Advancing Biological And Pharmaceutical Mass Spectrometry, Hao Chen, Yunlin Fu, Mei Han, Xianlin Han, Ling Hao, Tao Huan, Lan Huang, Ming Huang, Qin Ji, Tao Jiang, Yong Jiang, Liang Li, Lingjun Li, Xiaorong Liang, Mamie Lih, Yanping Lin, Xiaowen Liu, Tao Liu, Yansheng Liu, Shuguang Ma, Junmin Peng, Yue A Qi, Jun Qu, Wilson Shou, Liangliang Sun, Mingxun Wang, Shuai Wang, Ronghu Wu, Si Wu, Xin Yan, Jun Yang, Weiming Yang, Zhibo Yang, Yonghao Yu, Hui Zhang, Hui Zhang, Shouxun Zhao, Jiangjiang Zhu, Ying Zhu, Yinsheng Wang, Naidong Weng
Meeting Report On The 3rd Chinese American Society For Mass Spectrometry Conference-Advancing Biological And Pharmaceutical Mass Spectrometry, Hao Chen, Yunlin Fu, Mei Han, Xianlin Han, Ling Hao, Tao Huan, Lan Huang, Ming Huang, Qin Ji, Tao Jiang, Yong Jiang, Liang Li, Lingjun Li, Xiaorong Liang, Mamie Lih, Yanping Lin, Xiaowen Liu, Tao Liu, Yansheng Liu, Shuguang Ma, Junmin Peng, Yue A Qi, Jun Qu, Wilson Shou, Liangliang Sun, Mingxun Wang, Shuai Wang, Ronghu Wu, Si Wu, Xin Yan, Jun Yang, Weiming Yang, Zhibo Yang, Yonghao Yu, Hui Zhang, Hui Zhang, Shouxun Zhao, Jiangjiang Zhu, Ying Zhu, Yinsheng Wang, Naidong Weng
Faculty, Staff and Student Publications
Following the highly successful Chinese American Society for Mass Spectrometry (CASMS) conferences in the previous 2 years, the 3rd CASMS Conference was held virtually on August 28–31, 2023, using the Gather. Town platform to bring together scientists in the MS field. The conference offered a 4-day agenda with a scientific program consisting of two plenary lectures, and 14 parallel symposia in which a total of 70 speakers presented technological innovations and their applications in proteomics and biological MS and metabo-lipidomics and pharmaceutical MS. In addition, 16 invited speakers/panelists presented at two research-focused and three career development workshops. Moreover, 86 posters, …
A Scoping Review Of Fair Machine Learning Techniques When Using Real-World Data, Yu Huang, Jingchuan Guo, Wei-Han Chen, Hsin-Yueh Lin, Huilin Tang, Fei Wang, Hua Xu, Jiang Bian
A Scoping Review Of Fair Machine Learning Techniques When Using Real-World Data, Yu Huang, Jingchuan Guo, Wei-Han Chen, Hsin-Yueh Lin, Huilin Tang, Fei Wang, Hua Xu, Jiang Bian
Faculty, Staff and Student Publications
Objective: The integration of artificial intelligence (AI) and machine learning (ML) in health care to aid clinical decisions is widespread. However, as AI and ML take important roles in health care, there are concerns about AI and ML associated fairness and bias. That is, an AI tool may have a disparate impact, with its benefits and drawbacks unevenly distributed across societal strata and subpopulations, potentially exacerbating existing health inequities. Thus, the objectives of this scoping review were to summarize existing literature and identify gaps in the topic of tackling algorithmic bias and optimizing fairness in AI/ML models using real-world data …
Spec: A Soft Prompt-Based Calibration On Performance Variability Of Large Language Model In Clinical Notes Summarization, Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu
Spec: A Soft Prompt-Based Calibration On Performance Variability Of Large Language Model In Clinical Notes Summarization, Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu
Faculty, Staff and Student Publications
Electronic health records (EHRs) store an extensive array of patient information, encompassing medical histories, diagnoses, treatments, and test outcomes. These records are crucial for enabling healthcare providers to make well-informed decisions regarding patient care. Summarizing clinical notes further assists healthcare professionals in pinpointing potential health risks and making better-informed decisions. This process contributes to reducing errors and enhancing patient outcomes by ensuring providers have access to the most pertinent and current patient data. Recent research has shown that incorporating instruction prompts with large language models (LLMs) substantially boosts the efficacy of summarization tasks. However, we show that this approach also …