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Quantum-Inspired Acceleration for Image Reconstruction on Ising Machines

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Quantum-Inspired Acceleration for Image Reconstruction on Is...

Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Yen-Jui Chang Hao-Yuan Chen Ying Chang Lu Lien-Po Yu Chao-Ming Fu Ching-Ray Chang Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan Department of Physics National Taiwan University Taipei Taiwan Fujitsu Taiwan Ltd. Taipei Taiwan Department of Computer Science University of London London United Kingdom Institute for Information Industry Taipei Taiwan Fo Guang University Yilan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan

The study investigates a quantum-inspired approach to image reconstruction using Ising machines and demonstrates its significant improvements over the contrastive divergence method in Restricted Boltzmann Machines tra... 详细信息

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

关键词： Training Quantum computing Image reconstruction

Structured Downsampling for Fast, Memory-efficient Curation of Online data Streams

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arXiv 2024年

作者： Moreno, Matthew Andres Zaman, Luis Dolson, Emily Department of Ecology and Evolutionary Biology Ann Arbor United States Center for the Study of Complex Systems Ann Arbor United States Michigan Institute for Data and AI in Society Ann Arbor United States University of Michigan Ann Arbor United States Department of Computer Science and Engineering East Lansing United States Program in Ecology Evolution and Behavior East Lansing United States Michigan State University East Lansing United States

Operations over data streams typically hinge on efficient mechanisms to aggregate or summarize history on a rolling basis. For high-volume data steams, it is critical to manage state in a manner that is fast and memory efficient - particularly in resource-constrained or real-time contexts. Here, we address the problem of extracting a fixed-capacity, rolling subsample from a data stream. Specifically, we explore "data stream curation" strategies to fulfill requirements on the composition of sample time points retained. Our "DStream" suite of algorithms targets three temporal coverage criteria: (1) steady coverage, where retained samples should spread evenly across elapsed data stream history;(2) stretched coverage, where early data items should be proportionally favored;and (3) tilted coverage, where recent data items should be proportionally favored. For each algorithm, we prove worst-case bounds on rolling coverage quality. In contrast to previous work by Moreno, Rodriguez Papa, and Dolson (2024), which dynamically scales memory use to guarantee a specified level of coverage quality, here we focus on the more practical, application-driven case of maximizing coverage quality given a fixed memory capacity. As a core simplifying assumption, we restrict algorithm design to a single update operation: writing from the data stream to a calculated buffer site - with data never being read back, no metadata stored (e.g., sample timestamps), and data eviction occurring only implicitly via overwrite. Drawing only on primitive, low-level operations and ensuring full, overhead-free use of available memory, this "DStream" framework ideally suits domains that are resource-constrained (e.g., embedded systems), performance-critical (e.g., real-time), and fine-grained (e.g., individual data items as small as single bits or bytes). In particular, proposed power-of-two-based buffer layout schemes support O(1) data ingestion via concise bit-level operations. To further practical applica

关键词： data streams

International cooperation in cardiogenic shock is key to improving outcomes: Cardiogenic Shock Working Group impacts a single center in a developing country

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Journal of Heart and Lung Transplantation 2025年第7期44卷 1165-1171页

作者： Ortega-Hernández, Jorge A. González-Pacheco, Héctor Hernandez-Montfort, Jaime Araiza-Garaygordobil, Diego Manzur-Sandoval, Daniel Gopar-Nieto, Rodrigo Sierra-Lara-Martínez, Daniel Kanwar, Manreet Sinha, Shashank S. Garan, Arthur Reshad Burkhoff, Daniel Abraham, Jacob Kapur, Navin K. Arias-Mendoza, Alexandra Instituto Nacional de Cardiologia Ignacio Chavez Coronary Care Unit Ciudad De Mexico Mexico Central Texas Baylor Scott & White Health Advanced Heart Failure and Recovery Program Temple Texas United States Cardiovascular Institute at Allegheny Health Network Pittsburgh PA United States Inova Heart and Vascular Institute Cardiac Intensive Care Unit Fairfax Virginia United States Beth Israel Deaconess Medical Center Advanced Heart Failure and Transplant Cardiology Boston Massachusetts United States Cardiovascular Research Foundation Heart Failure Hemodynamics and MCS Research New York New York United States Providence Heart Institute Center for Cardiovascular Analytics Research and Data Science (CARDS) Providence St. Joseph Health Portland Oregon United States Tufts Medical Center Inc. Cardiovascular Center for Research and Innovation Boston Massachusetts United States

The Cardiogenic Shock Working Group (CSWG) is an international research consortium formed in 2016. The National Institute of Cardiology Ignacio Chavez joined in 2021 and launched a cardiogenic shock (CS) program in 2022. This study evaluates the impact of CSWG core standards on outcomes in a middle-income country reference center of 9,430 patients with CS (Society for Cardiovascular Angiography and Interventions [SCAI] stages B→E) from a registry of 28,054 admissions (2005–2023). Using multivariate Cox regression and propensity score matching, outcomes were compared between historic pre-CSWG (2005–2021) and contemporary pre-CSWG (2017–2021) eras vs the CSWG era (2022–2023). Adoption of CS-team standards increased the use of pulmonary artery catheters (4.2%, 4% vs 7.9%, p < 0.001) and mechanical circulatory support devices (8.1% to 10.3%, p = 0.014) only in the legacy era. Reducing mortality from 22.3% and 20.5% vs 15.3% (p < 0.001). The adjusted hazard ratio for mortality in the pre-CSWG era was 1.22 (p = 0.015) for the historical cohort and 1.20 (p = 0.047) for the contemporary cohort. CS-international collaboration enhanced outcomes through standardized protocols, advanced interventions, and dedicated CS teams, underscoring the importance of international cooperation in CS care. © 2025 International Society for the Heart and Lung Transplantation

关键词： cardiogenic shock international cooperation mechanical circulatory support pulmonary artery catheter shock teams

Multivariate Conway-Maxwell-Poisson distribution: Sarmanov method and doubly-intractable Bayesian inference

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arXiv 2021年

作者： Piancastelli, Luiza S.C. Friel, Nial Barreto-Souza, Wagner Ombao, Hernando School of Mathematics and Statistics University College Dublin Dublin Ireland Insight Centre for Data Analytics Ireland Statistics Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

In this paper, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for constructing multivariate distributions. Our multivariate COM-Poisson (MultCOMP) model has desirable features such as (i) it admits a flexible covariance matrix allowing for both negative and positive non-diagonal entries;(ii) it overcomes the limitation of the existing bivariate COM-Poisson distributions in the literature that do not have COM-Poisson marginals;(iii) it allows for the analysis of multivariate counts and is not just limited to bivariate counts. Inferential challenges are presented by the likelihood specification as it depends on a number of intractable normalizing constants involving the model parameters. These obstacles motivate us to propose a Bayesian inferential approach where the resulting doubly-intractable posterior is dealt with via the exchange algorithm and the Grouped Independence Metropolis-Hastings algorithm. Numerical experiments based on simulations are presented to illustrate the proposed Bayesian approach. We analyze the potential of the MultCOMP model through a real data application on the numbers of goals scored by the home and away teams in the Premier League from 2018 to 2021. Here, our interest is to assess the effect of a lack of crowds during the COVID-19 pandemic on the well-known home team advantage. A MultCOMP model fit shows that there is evidence of a decreased number of goals scored by the home team, not accompanied by a reduced score from the opponent. Hence, our analysis suggests a smaller home team advantage in the absence of crowds, which agrees with the opinion of several football experts. Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

LANDMARK ALTERNATING DIFFUSION

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arXiv 2024年

作者： Yeh, Sing-Yuan Wu, Hau-Tieng Talmon, Ronen Tsui, Mao-Pei Data Science Degree Program National Taiwan University Academia Sinica Taipei106 Taiwan Courant Institute of Mathematical Sciences New York University New YorkNY10012 United States Viterbi Faculty of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa3200003 Israel Department of Mathematics National Taiwan University Taipei106 Taiwan National Center for Theoretical Sciences Mathematics Division Taipei106 Taiwan

Alternating Diffusion (AD) is a commonly applied diffusion-based sensor fusion algorithm. While it has been successfully applied to various problems, its computational burden remains a limitation. Inspired by the landmark diffusion idea considered in the Robust and Scalable Embedding via Landmark Diffusion (ROSELAND), we propose a variation of AD, called Landmark AD (LAD), which captures the essence of AD while offering superior computational efficiency. We provide a series of theoretical analyses of LAD under the manifold setup and apply it to the automatic sleep stage annotation problem with two electroencephalogram channels to demonstrate its *** Codes 53Z50, 65D18 © 2024, CC BY.

关键词： Diffusion

High-Order Synchrosqueezed Chirplet Transforms for Multicomponent Signal Analysis

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arXiv 2024年

作者： Yen, Yi-Ju Lu, De-Yan Yeh, Sing-Yuan Ding, Jian-Jiun Shen, Chun-Yen Graduate Institute of Communication Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei10617 Taiwan Graduate Institute of Mathematics National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei10617 Taiwan Data Science Degree Program National Taiwan University Academia Sinica No. 1 Sec. 4 Roosevelt Rd. Taipei10617 Taiwan

This study focuses on the analysis of signals containing multiple components with crossover instantaneous frequencies (IF). This problem was initially solved with the chirplet transform (CT). Also, it can be sharpened by adding the synchrosqueezing step, which is called the synchrosqueezed chirplet transform (SCT). However, we found that the SCT goes wrong with the high chirp modulation signal due to the wrong estimation of the IF. In this paper, we present the improvement of the post-transformation of the CT. The main goal of this paper is to amend the estimation introduced in the SCT and carry out the high-order synchrosqueezed chirplet transform. The proposed method reduces the wrong estimation when facing a stronger variety of chirp-modulated multi-component signals. The theoretical analysis of the new reassignment ingredient is provided. Numerical experiments on some synthetic signals are presented to verify the effectiveness of the proposed high-order *** Codes 65T99, 42C99, 42a38 Copyright © 2024, The Authors. All rights reserved.

关键词： Chirp modulation

Language Enhanced Model for Eye (LEME): An Open-Source Ophthalmology-Specific Large Language Model

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arXiv 2024年

作者： Gilson, Aidan Ai, Xuguang Xie, Qianqian Srinivasan, Sahana Pushpanathan, Krithi Singer, Maxwell B. Huang, Jimin Kim, Hyunjae Long, Erping Wan, Peixing Del Priore, Luciano V. Ohno-Machado, Lucila Xu, Hua Liu, Dianbo Adelman, Ron A. Tham, Yih-Chung Chen, Qingyu Department of Ophthalmology Massachusetts Eye and Ear Harvard Medical School BostonMA United States Department of Biomedical Informatics and Data Science Yale School of Medicine Yale University New Haven United States Singapore Eye Research Institute Singapore National Eye Centre Singapore Centre for Innovation and Precision Eye Health Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore Department of Ophthalmology and Visual Science Yale School of Medicine Yale University New Haven United States Department of Computer Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health BethesdaMD United States Center for Cancer Research National Cancer Institute National Institutes of Health BethesdaMD United States Ophthalmology and Visual Science Academic Clinical Program Duke-NUS Medical School Singapore Singapore

Large Language Models (LLMs) are poised to revolutionize healthcare. Ophthalmology-specific LLMs remain scarce and underexplored. We introduced an open-source, specialized LLM for ophthalmology, termed Language Enhanced Model for Eye (LEME). LEME was initially pre-trained on the Llama2 70B framework and further fine-tuned with a corpus of ~127,000 non-copyrighted training instances curated from ophthalmology-specific case reports, abstracts, and open-source study materials. We benchmarked LEME against eight other LLMs, namely, GPT-3.5, GPT-4, three Llama2 models (7B, 13B, 70B), PMC-LLAMA 13B, Meditron 70B, and EYE-Llama (another ophthalmology-specific LLM). Evaluations included four internal validation tasks: abstract completion, fill-in-the-blank, multiple-choice questions (MCQ), and short-answer QA. External validation tasks encompassed long-form QA, MCQ, patient EHR summarization, and clinical QA. Evaluation metrics included Rouge-L scores, accuracy, and expert evaluation of correctness, completeness, and readability. In internal validations, LEME consistently outperformed its counterparts, achieving Rouge-L scores of 0.20 ± 0.03 in abstract completion (all p © 2024, CC BY.

关键词： Ophthalmology

Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias

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arXiv 2024年

作者： Ke, Yu He Yang, Rui Lie, Sui An Lim, Taylor Xin Yi Abdullah, Hairil Rizal Ting, Daniel Shu Wei Liu, Nan Department of Anesthesiology Singapore General Hospital Singapore Singapore Center for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Singapore Eye Research Institute Singapore National Eye Center Singapore Singapore Byers Eye Institute Stanford University StanfordCA United States Program in Health Services and Systems Research Duke-NUS Medical School Singapore Singapore Institute of Data Science National University of Singapore Singapore Singapore

Background: Cognitive biases in clinical decision-making significantly contribute to errors in diagnosis and suboptimal patient outcomes. Addressing these biases presents a formidable challenge in the medical field. Objective: This study explores the role of large language models (LLMs) in mitigating these biases through the utilization of a multi-agent framework. We simulate the clinical decision-making processes through multi-agent conversation and evaluate its efficacy in improving diagnostic accuracy. Methods: A total of 16 published and unpublished case reports where cognitive biases have resulted in misdiagnoses were identified from the literature. In the multi-agent framework, we leveraged GPT-4 to facilitate interactions among four simulated agents to replicate clinical team dynamics. Each agent has a distinct role: 1) To make the final diagnosis after considering the discussions, 2) The devil's advocate and correct confirmation and anchoring bias, 3) The tutor and facilitator of the discussion to reduce premature closure bias, and 4) To record and summarize the findings. A total of 80 simulations were evaluated for the accuracy of initial diagnosis, top differential diagnosis and final two differential diagnoses. Results: In a total of 80 responses evaluating both initial and final diagnoses, the initial diagnosis had an accuracy of 0% (0/80), but following multi-agent discussions, the accuracy for the top differential diagnosis increased to 71.3% (57/80), and for the final two differential diagnoses, to 80.0% (64/80). Conclusions: The framework demonstrated an ability to re-evaluate and correct misconceptions, even in scenarios with misleading initial investigations. The LLMdriven multi-agent conversation framework shows promise in enhancing diagnostic accuracy in diagnostically challenging medical scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Diagnosis

Artificial intelligence-assisted niacin skin flush screening in early psychosis identification and prediction

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General Psychiatry 2022年第2期35卷 76-78页

作者： Tao Chen Haichun Liu Renfang Tian Ranpiao Gan Wenzuo Xu Tianhong Zhang Jijun Wang Department of Economics University of WaterlooWaterlooOntarioCanada Depatment of Statistics and Actuarial Science(Cross Appointed) University of Waterloo WaterlooOntarioCanada Big Data Research Lab Universty of WaterlooWaterlooOntarioCanada Shanghai Niacin Tech Co. LtdShanghal China Labor and Worklife Program Harvard UniversityCambridgeMassachusettsUSA Department of Automation Shanghai Jao Tong UniversityShanghaiChina Ningbo Artificial Intelligent Institute Shanghai Jiao Tong UniversityNingboChina School of Management Economicsand MathematicsKing's University CollegeLondon0ntarioCanada Shanghai Intelligent Psychological Evaluaton and Intervention Engineering Technology Research Center Shanghai Key Laboratory of Psychotic DisordersShanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina Bio-X Institutes Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders(Ministry of Education)ShanghaiChina CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghaiChina Institute of Psychology and Behavioral Science Shanghai Jiao Tong UniversiyShanghaiChina

Schizophrenia is a devastating mental disorder affecting 20 million people *** diagnosis is crucial for disease management and improvement in prognosis,and diagnostic biomarkerscan serveasobjective indicators for the early screening of the *** on the observation of diminished flush responses to niacin in patients with schizophrenia Horrobin proposed anoninvasive niacin skin flush screening for schizophrenia.

关键词： diagnosis prognosis prediction