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Article ; Online: Describe, Spot and Explain: Interpretable Representation Learning for Discriminative Visual Reasoning.

Lin, Ci-Siang / Wang, Yu-Chiang Frank

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

2023 Volume 32, Page(s) 2481–2492

Abstract: Despite the recent success achieved by deep neural networks (DNNs), it remains challenging to disclose/explain the decision-making process from the numerous parameters and complex non-linear functions. To address the problem, explainable AI (XAI) aims to ...

Abstract	Despite the recent success achieved by deep neural networks (DNNs), it remains challenging to disclose/explain the decision-making process from the numerous parameters and complex non-linear functions. To address the problem, explainable AI (XAI) aims to provide explanations corresponding to the learning and prediction processes for deep learning models. In this paper, we propose a novel representation learning framework of Describe, Spot and eXplain (DSX). Based on the architecture of Transformer, our proposed DSX framework is composed of two learning stages, descriptive prototype learning and discriminative prototype discovery. Given an input image, the former stage is designed to derive a set of descriptive representations, while the latter stage further identifies a discriminative subset, offering semantic interpretability for the corresponding classification tasks. While our DSX does not require any ground truth attribute supervision during training, the derived visual representations can be practically associated with physical attributes provided by domain experts. Extensive experiments on fine-grained classification and person re-identification tasks qualitatively and quantitatively verify the use our DSX model for offering semantically practical interpretability with satisfactory recognition performances.
Language	English
Publishing date	2023-05-08
Publishing country	United States
Document type	Journal Article
ISSN	1941-0042
ISSN (online)	1941-0042
DOI	10.1109/TIP.2023.3268001
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Learning of 3D Graph Convolution Networks for Point Cloud Analysis.

Lin, Zhi-Hao / Huang, Sheng-Yu / Wang, Yu-Chiang Frank

IEEE transactions on pattern analysis and machine intelligence

2022 Volume 44, Issue 8, Page(s) 4212–4224

Abstract: Point clouds are among the popular geometry representations in 3D vision. However, unlike 2D images with pixel-wise layouts, such representations containing unordered data points which make the processing and understanding the associated semantic ... ...

Abstract	Point clouds are among the popular geometry representations in 3D vision. However, unlike 2D images with pixel-wise layouts, such representations containing unordered data points which make the processing and understanding the associated semantic information quite challenging. Although a number of previous works attempt to analyze point clouds and achieve promising performances, their performances would degrade significantly when data variations like shift and scale changes are presented. In this paper, we propose 3D graph convolution networks (3D-GCN), which uniquely learns 3D kernels with graph max-pooling mechanisms for extracting geometric features from point cloud data across different scales. We show that, with the proposed 3D-GCN, satisfactory shift and scale invariance can be jointly achieved. We show that 3D-GCN can be applied to point cloud classification and segmentation tasks, with ablation studies and visualizations verifying the design of 3D-GCN.
Language	English
Publishing date	2022-07-01
Publishing country	United States
Document type	Journal Article
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2021.3059758
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Book ; Online: Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser

Lai, Yung-Hsuan / Chen, Yen-Chun / Wang, Yu-Chiang Frank

2023

Abstract: Audio-visual learning has been a major pillar of multi-modal machine learning, where the community mostly focused on its modality-aligned setting, i.e., the audio and visual modality are both assumed to signal the prediction target. With the Look, Listen, ...

Abstract	Audio-visual learning has been a major pillar of multi-modal machine learning, where the community mostly focused on its modality-aligned setting, i.e., the audio and visual modality are both assumed to signal the prediction target. With the Look, Listen, and Parse dataset (LLP), we investigate the under-explored unaligned setting, where the goal is to recognize audio and visual events in a video with only weak labels observed. Such weak video-level labels only tell what events happen without knowing the modality they are perceived (audio, visual, or both). To enhance learning in this challenging setting, we incorporate large-scale contrastively pre-trained models as the modality teachers. A simple, effective, and generic method, termed Visual-Audio Label Elaboration (VALOR), is innovated to harvest modality labels for the training events. Empirical studies show that the harvested labels significantly improve an attentional baseline by 8.0 in average F-score (Type@AV). Surprisingly, we found that modality-independent teachers outperform their modality-fused counterparts since they are noise-proof from the other potentially unaligned modality. Moreover, our best model achieves the new state-of-the-art on all metrics of LLP by a substantial margin (+5.4 F-score for Type@AV). VALOR is further generalized to Audio-Visual Event Localization and achieves the new state-of-the-art as well. Code is available at: https://github.com/Franklin905/VALOR. Comment: NeurIPS 2023
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Sound ; Electrical Engineering and Systems Science - Audio and Speech Processing
Subject code	700
Publishing date	2023-05-26
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: FedBug

Kao, Chia-Hsiang / Wang, Yu-Chiang Frank

A Bottom-Up Gradual Unfreezing Framework for Federated Learning

2023

Abstract: Federated Learning (FL) offers a collaborative training framework, allowing multiple clients to contribute to a shared model without compromising data privacy. Due to the heterogeneous nature of local datasets, updated client models may overfit and ... ...

Abstract	Federated Learning (FL) offers a collaborative training framework, allowing multiple clients to contribute to a shared model without compromising data privacy. Due to the heterogeneous nature of local datasets, updated client models may overfit and diverge from one another, commonly known as the problem of client drift. In this paper, we propose FedBug (Federated Learning with Bottom-Up Gradual Unfreezing), a novel FL framework designed to effectively mitigate client drift. FedBug adaptively leverages the client model parameters, distributed by the server at each global round, as the reference points for cross-client alignment. Specifically, on the client side, FedBug begins by freezing the entire model, then gradually unfreezes the layers, from the input layer to the output layer. This bottom-up approach allows models to train the newly thawed layers to project data into a latent space, wherein the separating hyperplanes remain consistent across all clients. We theoretically analyze FedBug in a novel over-parameterization FL setup, revealing its superior convergence rate compared to FedAvg. Through comprehensive experiments, spanning various datasets, training conditions, and network architectures, we validate the efficacy of FedBug. Our contributions encompass a novel FL framework, theoretical analysis, and empirical validation, demonstrating the wide potential and applicability of FedBug. Comment: 20 pages, 5 figures
Keywords	Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2023-07-19
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Alternate Antimicrobial Therapies and Their Companion Tests.

Kalpana, Sriram / Lin, Wan-Ying / Wang, Yu-Chiang / Fu, Yiwen / Wang, Hsin-Yao

Diagnostics (Basel, Switzerland)

2023 Volume 13, Issue 15

Abstract: New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with the emergence of resistance, resulting in unsuccessful trials. The lack of an effective drug developed from the conventional ... ...

Abstract	New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with the emergence of resistance, resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies with clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers, and phages. Clinical diagnostics optimize the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic-based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious diseases include detection, monitoring of response, and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy, this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives with the use of alternate therapeutics, with a particular focus on companion diagnostic applications in infectious diseases.
Language	English
Publishing date	2023-07-26
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics13152490
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Article: Antibiotic Resistance Diagnosis in ESKAPE Pathogens-A Review on Proteomic Perspective.

Kalpana, Sriram / Lin, Wan-Ying / Wang, Yu-Chiang / Fu, Yiwen / Lakshmi, Amrutha / Wang, Hsin-Yao

Diagnostics (Basel, Switzerland)

2023 Volume 13, Issue 6

Abstract: Antibiotic resistance has emerged as an imminent pandemic. Rapid diagnostic assays distinguish bacterial infections from other diseases and aid antimicrobial stewardship, therapy optimization, and epidemiological surveillance. Traditional methods ... ...

Abstract	Antibiotic resistance has emerged as an imminent pandemic. Rapid diagnostic assays distinguish bacterial infections from other diseases and aid antimicrobial stewardship, therapy optimization, and epidemiological surveillance. Traditional methods typically have longer turn-around times for definitive results. On the other hand, proteomic studies have progressed constantly and improved both in qualitative and quantitative analysis. With a wide range of data sets made available in the public domain, the ability to interpret the data has considerably reduced the error rates. This review gives an insight on state-of-the-art proteomic techniques in diagnosing antibiotic resistance in ESKAPE pathogens with a future outlook for evading the "imminent pandemic".
Language	English
Publishing date	2023-03-07
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics13061014
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Article ; Online: Amiodarone is associated with increased short-term mortality in elderly atrial fibrillation patients with preserved ejection fraction.

Li, Weijia / Wang, Yu-Chiang / Tiwari, Nidhish / Di Biase, Luigi

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing

2021 Volume 63, Issue 1, Page(s) 207–214

Abstract: Purpose: Amiodarone is commonly used in atrial fibrillation (AF). Long-term use of amiodarone is associated with significant toxicities especially in elderly patients. However, in the short term after hospitalization of AF, it remains uncertain whether ... ...

Abstract	Purpose: Amiodarone is commonly used in atrial fibrillation (AF). Long-term use of amiodarone is associated with significant toxicities especially in elderly patients. However, in the short term after hospitalization of AF, it remains uncertain whether the use of amiodarone will increase mortality. We aim to investigate whether Amiodarone affects short-term mortality in elderly patients after hospitalization for atrial fibrillation. Methods: We conducted a single-center retrospective cohort study including patients (Age > = 60 years old) who were hospitalized between 07/01/2004 and 06/30/2019 with primary diagnosis of AF and left ventricular ejection fraction (LVEF) > = 50%. Patients who were prescribed amiodarone during hospitalization but not before hospitalization are classified into Amiodarone group (341 patients). Patients who were not prescribed amiodarone are classified into non-amiodarone group (2171 patients). Propensity score matching was performed with 1:1 nearest-neighbor matching of Amiodarone group and Non-amiodarone group based on baseline variables. Univariate and Multivariate logistic regression were used to calculate the odds ratio of amiodarone use on in-hospital mortality, and multivariate cox regression was adopted to calculate the hazard ratio of amiodarone use on 100-day mortality. Results: Patients' baseline demographic and clinical characteristics were well matched in both groups. Both univariate and multivariate logistic regression showed amiodarone group had higher in-hospital mortality (OR 10.27, p = 0.0268; 16.50, p = 0.0171) than non-amiodarone group and multivariate Cox regression suggested increased 100-day all-cause mortality (HR 2.34, p = 0.022). Conclusion: Amiodarone use in elderly patients with preserved ejection fraction is associated with increased in-hospital and 100-day all-cause mortality after hospitalization for AF.
MeSH term(s)	Aged ; Amiodarone/adverse effects ; Anti-Arrhythmia Agents/therapeutic use ; Atrial Fibrillation/drug therapy ; Humans ; Middle Aged ; Retrospective Studies ; Stroke Volume ; Ventricular Function, Left
Chemical Substances	Anti-Arrhythmia Agents ; Amiodarone (N3RQ532IUT)
Language	English
Publishing date	2021-02-26
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1329179-8
ISSN	1572-8595 ; 1383-875X
ISSN (online)	1572-8595
ISSN	1383-875X
DOI	10.1007/s10840-021-00970-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Trend of HPV Molecular Epidemiology in the Post-Vaccine Era: A 10-Year Study.

Lin, Yueh / Lin, Wan-Ying / Lin, Ting-Wei / Tseng, Yi-Ju / Wang, Yu-Chiang / Yu, Jia-Ruei / Chung, Chia-Ru / Wang, Hsin-Yao

Viruses

2023 Volume 15, Issue 10

Abstract: Cervical cancer, a major health concern among women worldwide, is closely linked to human papillomavirus (HPV) infection. This study explores the evolving landscape of HPV molecular epidemiology in Taiwan over a decade (2010-2020), where prophylactic HPV ...

Abstract	Cervical cancer, a major health concern among women worldwide, is closely linked to human papillomavirus (HPV) infection. This study explores the evolving landscape of HPV molecular epidemiology in Taiwan over a decade (2010-2020), where prophylactic HPV vaccination has been implemented since 2007. Analyzing data from 40,561 vaginal swab samples, with 42.0% testing positive for HPV, we reveal shifting trends in HPV genotype distribution and infection patterns. The 12 high-risk genotypes, in order of decreasing percentage, were HPV 52, 58, 16, 18, 51, 56, 39, 59, 33, 31, 45, and 35. The predominant genotypes were HPV 52, 58, and 16, accounting for over 70% of cases annually. The proportions of high-risk and non-high-risk HPV infections varied across age groups. High-risk infections predominated in sexually active individuals aged 30-50 and were mixed-type infections. The composition of high-risk HPV genotypes was generally stable over time; however, HPV31, 33, 39, and 51 significantly decreased over the decade. Of the strains, HPV31 and 33 are shielded by the nonavalent HPV vaccine. However, no reduction was noted for the other seven genotypes. This study offers valuable insights into the post-vaccine HPV epidemiology. Future investigations should delve into HPV vaccines' effects and their implications for cervical cancer prevention strategies. These findings underscore the need for continued surveillance and research to guide effective public health interventions targeting HPV-associated diseases.
MeSH term(s)	Humans ; Female ; Uterine Cervical Neoplasms/epidemiology ; Uterine Cervical Neoplasms/prevention & control ; Human Papillomavirus Viruses ; Papillomavirus Infections/epidemiology ; Papillomavirus Infections/prevention & control ; Molecular Epidemiology ; Papillomavirus Vaccines ; Papillomaviridae/genetics ; Genotype ; Human papillomavirus 31/genetics ; Prevalence
Chemical Substances	Papillomavirus Vaccines
Language	English
Publishing date	2023-09-27
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v15102015
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Article: Risk Stratification for Herpes Simplex Virus Pneumonia Using Elastic Net Penalized Cox Proportional Hazard Algorithm with Enhanced Explainability.

Wang, Yu-Chiang / Lin, Wan-Ying / Tseng, Yi-Ju / Fu, Yiwen / Li, Weijia / Huang, Yu-Chen / Wang, Hsin-Yao

Journal of clinical medicine

2023 Volume 12, Issue 13

Abstract: Herpes simplex virus (HSV) pneumonia is a serious and often fatal respiratory tract infection that occurs in immunocompromised individuals. The early detection of accurate risk stratification is essential in identifying patients who are at high risk of ... ...

Abstract	Herpes simplex virus (HSV) pneumonia is a serious and often fatal respiratory tract infection that occurs in immunocompromised individuals. The early detection of accurate risk stratification is essential in identifying patients who are at high risk of mortality and may benefit from more aggressive treatment. In this study, we developed and validated a risk stratification model for HSV bronchopneumonia using an elastic net penalized Cox proportional hazard algorithm. We analyzed data from a cohort of 104 critically ill patients with HSV bronchopneumonia identified in Chang Gung Memorial Hospital, Linkou, Taiwan: one of the largest tertiary medical centers in the world. A total of 109 predictors, both clinical and laboratory, were identified in this process to develop a risk stratification model that could accurately predict mortality in patients with HSV bronchopneumonia. This model was able to differentiate the risk of death and predict mortality in patients with HSV bronchopneumonia compared to the APACHE II score in the early stage of ICU admissions. Both hazard ratio coefficient and selection frequency were used as the metrics to enhance the explainability of the informative predictors. Our findings suggest that the elastic net penalized Cox proportional hazard algorithm is a promising tool for risk stratification in patients with HSV bronchopneumonia and could be useful in identifying those at high risk of mortality.
Language	English
Publishing date	2023-07-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm12134489
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Article ; Online: Visit to Visit Hemoglobin A1c Variation and Long-term Risk of Major Adverse Limb Events in Patients With Type 2 Diabetes.

Hsiao, Fu-Chih / Chan, Yi-Hsin / Tung, Ying-Chang / Lin, Chia-Pin / Lee, Ting-Hein / Wang, Yu-Chiang / Chu, Pao-Hsien

The Journal of clinical endocrinology and metabolism

2023 Volume 108, Issue 10, Page(s) 2500–2509

Abstract: Context: Glycemic variation had been demonstrated to be associated with several complications of diabetes.: Objective: Investigation of the association between visit to visit hemoglobin A1c (HbA1c) variation and the long-term risk of major adverse ... ...

Abstract	Context: Glycemic variation had been demonstrated to be associated with several complications of diabetes. Objective: Investigation of the association between visit to visit hemoglobin A1c (HbA1c) variation and the long-term risk of major adverse limb events (MALEs). Methods: Retrospective database study. Average real variability was used to represent glycemic variations with all the HbA1c measurements during the 4 following years after the initial diagnosis of type 2 diabetes. Participants were followed from the beginning of the fifth year until death or the end of the follow-up. The association between HbA1c variations and MALEs was evaluated after adjusting for mean HbA1c and baseline characteristics. Included were 56 872 patients at the referral center with a first diagnosis of type 2 diabetes, no lower extremity arterial disease, and at least 1 HbA1c measurement in each of the 4 following years were identified from a multicenter database. The main outcome measure was incidence of a MALE, which was defined as the composite of revascularization, foot ulcers, and lower limb amputations. Results: The average number of HbA1c measurements was 12.6. The mean follow-up time was 6.1 years. The cumulative incidence of MALEs was 9.25 per 1000 person-years. Visit to visit HbA1c variations were significantly associated with MALEs and lower limb amputation after multivariate adjustment. People in the highest quartile of variations had increased risks for MALEs (HR 1.25, 95% CI 1.10-1.41) and lower limb amputation (HR 3.05, 95% CI 1.97-4.74). Conclusion: HbA1c variation was independently associated with a long-term risk of MALEs and lower limb amputations in patients with type 2 diabetes.
MeSH term(s)	Male ; Humans ; Diabetes Mellitus, Type 2/complications ; Diabetes Mellitus, Type 2/epidemiology ; Diabetes Mellitus, Type 2/diagnosis ; Glycated Hemoglobin ; Risk Factors ; Retrospective Studies ; Blood Glucose ; Lower Extremity/surgery
Chemical Substances	Glycated Hemoglobin ; Blood Glucose
Language	English
Publishing date	2023-04-06
Publishing country	United States
Document type	Multicenter Study ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	3029-6
ISSN	1945-7197 ; 0021-972X
ISSN (online)	1945-7197
ISSN	0021-972X
DOI	10.1210/clinem/dgad203
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