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A survey of explainable artificial intelligence in healthcare: Concepts, applications, and challenges

Informatics in Medicine Unlocked 2024年 51卷

作者： Mienye, Ibomoiye Domor Obaido, George Jere, Nobert Mienye, Ebikella Aruleba, Kehinde Emmanuel, Ikiomoye Douglas Ogbuokiri, Blessing Institute for Intelligent Systems University of Johannesburg Auckland Park Johannesburg 2006 South Africa Center for Human-Compatible Artificial Intelligence (CHAI) Berkeley Institute for Data Science (BIDS) University of California Berkeley 94720 CA United States Department of Computer Science University of Fort Hare Alice Campus Eastern Cape Alice South Africa School of Computing and Mathematical Sciences University of Leicester Leicester LE1 7RH United Kingdom School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Computer Science Brock University Niagara Region St. Catharines L2S 3A1 ON Canada

Explainable AI (XAI) has the potential to transform healthcare by making AI-driven medical decisions more transparent, reliable, and ethically compliant. Despite its promise, the healthcare sector faces several challenges, including the need to balance interpretability and accuracy, integrating XAI into clinical workflows, and ensuring adherence to rigorous regulatory standards. This paper provides a comprehensive review of XAI in healthcare, covering techniques, challenges, opportunities, and advancements, thereby enhancing the understanding and practical application of XAI in healthcare. The study also explores responsible AI in healthcare, discussing new perspectives and emerging trends, offering valuable insights for researchers and practitioners. The insights and recommendations presented aim to guide future research and policy-making, fostering the development of transparent, trustworthy, and effective AI-driven solutions. © 2024 The Authors

关键词： AI Bias Ethics Fairness Healthcare Machine learning

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Improving the lifestyle behavior of type 2 diabetes mellitus patients using a mobile application

Improving the lifestyle behavior of type 2 diabetes mellitus...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Andreia Pinto João Viana Diogo Martinho Vítor Crista José Miguel Diniz Joana Reis João Matos David Greer Goreti Marreiros Alberto Freitas Department of Community Medicine Information and Health Decision Sciences (MEDCIDS) Faculty of Medicine Center for Health Technology and Services Research (CINTESIS) University of Porto Porto Portugal Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Institute of Engineering Polytechnic of Porto Porto Portugal Health Data Science PhD Program Faculty of Medicine Center for Health Technology and Services Research (CINTESIS) University of Porto Lisboa Portugal CLOO - Behavioral Insights Unit Faculty of Psychology CICPSI - Research Center for Psychological Science University of Lisbon Lisboa Portugal Behavioral Insights Unit CLOO Porto Portugal Behavioral Insights Unit CLOO Lisboa Portugal

ISBN: (数字)9781665497923

ISBN: (纸本)9781665497930

Type 2 diabetes is an increasingly prevalent disease and patients do not always manage the disease properly. Therefore, creating tools that help diabetics self-manage their condition over time is of the utmost importance. Technological tools that include features meeting this population's needs, with an integrated personalized feedback system, in an environment of gamified incentives, may be the way for developing a sustained app's usage. This work aims to present a still in development, novel approach to managing diabetes type 2 with a focus on data analysis from user-inputs, gamification, and personalized coaching, with an accessible user interface. Thus, we will present some functionalities, in particular the theoretical and practical concept that is behind this development, namely the Transtheoretical model of behavior change to create different profiles, to provide customized feedback according to the user's behavioral stage, and also to ascertain if it induces any improvement at the behavioral level.

关键词： Computers data analysis Computational modeling User interfaces Diabetes Behavioral sciences Mobile applications

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Social media emotion macroscopes reflect emotional experiences in society at large

arXiv

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arXiv 2021年

作者： Garcia, David Pellert, Max Lasser, Jana Metzler, Hannah Graz University of Technology Institute of Interactive Systems and Data Science Department of Computer Science and Biomedical Engineering Graz8010 Austria Complexity Science Hub Vienna Vienna1080 Austria Medical University of Vienna Center for Medical Statistics Informatics and Intelligent Systems Vienna1090 Austria Medical University of Vienna Department of Social and Preventive Medicine Center for Public Health Vienna1090 Austria

Social media generate data on human behaviour at large scales and over long periods of time, posing a complementary approach to traditional methods in the social sciences1. Millions of texts from social media can be processed with computational methods to study emotions2,3 over time and across regions4,5. However, recent research has shown weak correlations between social media emotions and affect questionnaires at the individual level6,7 and between static regional aggregates of social media emotion and subjective well-being at the population level8, questioning the validity of social media data to study emotions. Yet, to date, no research has tested the validity of social media emotion macroscopes to track the temporal evolution of emotions at the level of a whole society. Here we present a pre-registered prediction study that shows how gender-rescaled time series of Twitter emotional expression at the national level substantially correlate with aggregates of self-reported emotions in a weekly representative survey in the United Kingdom. A follow-up exploratory analysis shows a high prevalence of third-person references in emotionally-charged tweets, indicating that social media data provide a way of social sensing the emotions of others9 rather than just the emotional experiences of users. These results show that, despite the issues that social media have in terms of representativeness10 and algorithmic confounding11, the combination of advanced text analysis methods with user demographic information in social media emotion macroscopes can provide measures that are informative of the general population beyond social media users. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

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Investigating the Potential of Hydrogen Plasma Treated ALD-TiOx Films as Hole-selective Passivating Contacts in Crystalline Silicon Solar Cells

Investigating the Potential of Hydrogen Plasma Treated ALD-T...

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IEEE Conference Photovoltaic Specialists (PVSC)

作者： Chien-Hsuan Chen S. Novia Berriel Taylor M. Currie Jannatul Ferdous Mousumi Titel Jurca Parag Banerjee Kristopher O. Davis Department of Materials Science and Engineering University of Central Florida Orlando FL United States Department of Chemistry University of Central Florida Orlando FL United States Resilient Intelligent Sustainable Energy Systems Faculty Cluster University of Central Florida Orlando FL United States Florida Solar Energy Center University of Central Florida Orlando FL United States CREOL College of Optics and Photonics University of Central Florida Orlando FL United States

The potential of hydrogen plasma treated atomic layer deposited (ALD) titanium oxide (TiOx) films as hole-selective passivating contacts in crystalline silicon (c-Si) solar cells is discussed from three aspects including the passivation quality, carrier selectivity and electrical property. In this work, we also propose an integrated deposition technique through incorporating hydrogen plasma pulses into the thin film deposition. The passivation quality, carrier selectivity and electrical property were studied through photoluminescence (PL) image analysis, Schottky barrier height analysis using dark current-voltage/capacitance-voltage (I-V/C-V) measurements and contact resistivity analysis using transmission line method (TLM). Compared with conventional deposition techniques and post-treatments, high passivation quality, excellent carrier selectivity and low contact resistivity can be achieved through combining our integrated deposition technique with post hydrogen plasma treatment (HPT). Further study will be performed to evaluate the durability and reliability of TiOx contacts in c-Si solar cells. Index Terms-atomic layer deposition, titanium oxide, passivation quality, carrier selectivity, contact resistivity, passivating contact, hole-selective contact, hydrogen plasma

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Enhanced Visual Feedback with Decoupled Viewpoint Control in Immersive Humanoid Robot Teleoperation using SLAM

Enhanced Visual Feedback with Decoupled Viewpoint Control in...

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IEEE-RAS International Conference on Humanoid Robots

作者： Yang Chen Leyuan Sun Mehdi Benallegue Rafael Cisneros-Limón Rohan P. Singh Kenji Kaneko Arnaud Tanguy Guillaume Caron Kenji Suzuki Abderrahmane Kheddar Fumio Kanehiro School of Integrative and Global Majors (SIGMA) University of Tsukuba Japan CNRS-AIST JRL (Joint Robotics Laboratory) IRL National Institute of Advanced Industrial Science and Technology (AIST) Department of Intelligent and Mechanical Interaction Systems Graduate School of Science and Technology University of Tsukuba Japan MIS lab Universite de Picardie Jules Verne Amiens France Faculty of Engineering and Center for Cybernetics Research University of Tsukuba Japan

ISBN: (数字)9798350309799

ISBN: (纸本)9798350309805

In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: (i) the lag between the motion of the operator's and robot's head due to network communication delays or slow robot joint motion. This latency could cause a noticeable delay in the visual feedback, which jeopardizes the embodiment quality, can cause dizziness, and affects the interactivity resulting in operator frequent motion pauses for the visual feedback to settle; (ii) the mismatch between the camera's and the headset's field-of-views (FOV), the former having generally a lower FOV; and (iii) a mismatch between human's and robot's range of motions of the neck, the latter being also generally lower. In order to leverage these draw-backs, we developed a decoupled viewpoint control solution for a humanoid platform which allows visual feedback with low-latency and artificially increases the camera's FOV range to match that of the operator's headset. Our novel solution uses SLAM technology to enhance the visual feedback from a reconstructed mesh, complementing the areas that are not covered by the visual feedback from the robot. The visual feedback is presented as a point cloud in real-time to the operator. As a result, the operator is fed with real-time vision from the robot's head orientation by observing the pose of the point cloud. Balancing this kind of awareness and immersion is important in virtual reality based teleoperation, considering the safety and robustness of the control system. An experiment shows that the effectiveness of our solution.

关键词： Point cloud compression Visualization Simultaneous localization and mapping Humanoid robots Virtual reality Real-time systems Robustness

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FCM-DNN: diagnosing coronary artery disease by deep accuracy fuzzy C-means clustering model

arXiv

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arXiv 2022年

作者： Joloudari, Javad Hassannataj Saadatfar, Hamid GhasemiGol, Mohammad Alizadehsani, Roohallah Sani, Zahra Alizadeh Hasanzadeh, Fereshteh Hassannataj, Edris Sharifrazi, Danial Mansor, Zulkefli Department of Computer Engineering Faculty of Engineering University of Birjand Birjand Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia Rajaie Cardiovascular Medical and Research Center Iran University of Medical Sciences Tehran Iran Omid Hospital Iran University of Medical Sciences Tehran Iran Department of Nursing School of Nursing and Allied Medical Sciences Maragheh Faculty of Medical Sciences Maragheh Iran Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Faculty of Information Science and Technology Universiti Kebangsaan Malaysia UKM Bangi43600 Malaysia

Cardiovascular disease is one of the most challenging diseases in middle-aged and older people, which causes high mortality. Coronary artery disease (CAD) is known as a common cardiovascular disease. A standard clinical tool for diagnosing CAD is angiography. The main challenges are dangerous side effects and high angiography costs. Today, the development of artificial intelligence-based methods is a valuable achievement for diagnosing disease. Hence, in this paper, artificial intelligence methods such as neural network (NN), deep neural network (DNN), and fuzzy C-means clustering combined with deep neural network (FCM-DNN) are developed for diagnosing CAD on a cardiac magnetic resonance imaging (CMRI) dataset. The original dataset is used in two different approaches. First, the labeled dataset is applied to the NN and DNN to create the NN and DNN models. Second, the labels are removed, and the unlabeled dataset is clustered via the FCM method, and then, the clustered dataset is fed to the DNN to create the FCM-DNN model. By utilizing the second clustering and modeling, the training process is improved, and consequently, the accuracy is increased. As a result, the proposed FCM-DNN model achieves the best performance with a 99.91% accuracy specifying 10 clusters, i.e., 5 clusters for healthy subjects and 5 clusters for sick subjects, through the 10-fold cross-validation technique compared to the NN and DNN models reaching the accuracies of 92.18% and 99.63%, respectively. To the best of our knowledge, no study has been conducted for CAD diagnosis on the CMRI dataset using artificial intelligence methods. The results confirm that the proposed FCM-DNN model can be helpful for scientific and research centers. © 2022, CC BY-SA.

关键词： Diseases

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

SSRN

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Image inpainting based on image structure and texture decomposition

Image inpainting based on image structure and texture decomp...

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International Conference on Mechatronics and intelligent Robotics, ICMIR 2018

作者： Qiang, Zhenping Liu, Hui Shang, Zhenhong College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

ISBN: (纸本)9783030002138

Image inpainting is a major research content in the field of computer vision and is intended to solve the problem of high-quality repairing of the damaged images automatically. In this paper, considering the image containing structural component and texture component generally, an Adaptive Local Laplacian Filter (ALLF) is first proposed to decompose the image, and the different components obtained through ALLF decomposition are further repaired by different methods. The restoration results are added together to achieve the completion of the whole image. Experiments on synthetic and natural images show the advantages of our approach, especially, in small scratch repair and text removal task. © Springer Nature Switzerland AG 2019.

关键词： Textures

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SMART COMMUNICATIONS AND NETWORKING FOR FUTURE DEEP-SPACE EXPLORATION

引用

China Communications 2020年第7期17卷 I0001-I0004页

作者： Qinyu Zhang Zhili Sun Tomaso de Cola Kanglian Zhao the EIE School the Institute for Communication Systems(ICS) Department of Electrical and Electronic EngineeringFaculty of Engineering and Physical SciencesUniversity of Surrey the German Aerospace Center(DLR) the Satellite and Space Communications(SSC)technical committee within ComSoc the Space-Internetworking Services(SIS)within the CCSDS standardization body the SatCom working group within the ETP Networld2020 platform School of Electronic Science and Engineering Nanjing University Institute of Space-Terrestrial Intelligent Networks Nanjing University

Since the first space probe flew to the Moon in 1959,over 200 deep-space exploration missions have already been carried out on the eight planets,various asteroids and comets in the solar *** of deepspace scientific ex... 详细信息

关键词： SPACE planet NETWORK

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PDADMAC/Alginate-Coated Gold Nanorod For Eradication of Staphylococcus Aureus Biofilms

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International journal of nanomedicine 2024年 19卷 3697-3714页

作者： Malarmugila Manimaran Yin Yin Teo James Chen Yong Kah Adilet Beishenaliev Yean Leng Loke Yiing Yee Foo Shiow-Fern Ng Chin Fei Chee Sek Peng Chin Farid Nazer Faruqu Chia-Yu Chang Misni Misran Lip Yong Chung Bey Fen Leo Shih-Hwa Chiou Chia-Ching Chang Sun Tee Tay Lik Voon Kiew Department of Pharmacology Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia. Department of Chemistry Faculty of Science Universiti Malaya Kuala Lumpur Malaysia. Department of Biomedical Engineering College of Design and Engineering National University of Singapore Singapore Singapore. Centre for Drug Delivery Technology and Vaccine Faculty of Pharmacy Universiti Kebangsaan Malaysia Kuala Lumpur Malaysia. Nanotechnology Catalysis Research Centre Universiti Malaya Kuala Lumpur Malaysia. Department of Pharmaceutical Chemistry Faculty of Pharmacy Universiti Malaya Kuala Lumpur Malaysia. Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Republic of China. Department of Molecular Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia. Department of Medical Research Taipei Veterans General Hospital Taipei Taiwan Republic of China. Institute of Pharmacology National Yang Ming Chiao Tung University Taipei Taiwan Republic of China. Department of Electrophysics National Yang Ming Chiao Tung University Hsinchu Taiwan Republic of China. Center for Intelligent Drug Systems and Smart Bio-devices National Yang Ming Chiao Tung University Hsinchu Taiwan Republic of China. Institute of Physics Academia Sinica Nankang Taipei Taiwan Republic of China. Department of Medical Microbiology Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia.

Introduction:Over 75% of clinical microbiological infections are caused by bacterial biofilms that grow on wounds or implantable medical devices. This work describes the development of a new poly(diallyldimethylammonium chloride) (PDADMAC)/alginate-coated gold nanorod (GNR/Alg/PDADMAC) that effectively disintegrates the biofilms of (), a prominent pathogen responsible for hospital-acquired infections. Methods:GNR was synthesised via seed-mediated growth method, and the resulting nanoparticles were coated first with Alg and then PDADMAC. FTIR, zeta potential, transmission electron microscopy, and UV-Vis spectrophotometry analysis were performed to characterise the nanoparticles. The efficacy and speed of the non-coated GNR and GNR/Alg/PDADMAC in disintegrating -preformed biofilms, as well as their in vitro biocompatibility (L929 murine fibroblast) were then studied. Results:The synthesised GNR/Alg/PDADMAC (mean length: 55.71 ± 1.15 nm, mean width: 23.70 ± 1.13 nm, aspect ratio: 2.35) was biocompatible and potent in eradicating preformed biofilms of methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) when compared to triclosan, an antiseptic used for disinfecting colonisation on abiotic surfaces in the hospital. The minimum biofilm eradication concentrations of GNR/Alg/PDADMAC (MBEC for MRSA biofilm = 0.029 nM; MBEC for MSSA biofilm = 0.032 nM) were significantly lower than those of triclosan (MBEC for MRSA biofilm = 10,784 nM; MBEC for MRSA biofilm 5967 nM). Moreover, GNR/Alg/PDADMAC was effective in eradicating 50% of MRSA and MSSA biofilms within 17 min when used at a low concentration (0.15 nM), similar to triclosan at a much higher concentration (50 µM). Disintegration of MRSA and MSSA biofilms was confirmed by field emission scanning electron microscopy and confocal laser scanning microscopy. Conclusion:These findings support the potential application of GNR/Alg/PDADMAC as an alternative agent to conventional antiseptics and antibiotics for the er

关键词： MRSA MSSA PDADMAC S. aureus biofilm gold nanorod

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