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A review of mobile chatbot apps for anxiety and depression and their self-care features

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Computer Methods and Programs in Biomedicine Update 2021年 1卷

作者： Ahmed, Arfan Ali, Nashva Aziz, Sarah Abd-alrazaq, Alaa A Hassan, Asmaa Khalifa, Mohamed Elhusein, Bushra Ahmed, Maram Ahmed, Mohamed Ali Siddig Househ, Mowafa Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Centre for Health Informatics Australian Institute of Health Innovation Faculty of Medicine Health and Human Sciences Macquarie University Sydney Australia Mental Health Services Hamad Medical Corporation Qatar

Background: Anxiety and depression rates are at an all-time high. Smartphone-based mental health chatbots can aid psychiatrists replacing some of the costly human based interaction providing a unique opportunity to expand the availability and quality of mental health intervention whilst providing an alternative approach to fill the much-needed self-care gap. Objective: Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. Methods: A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbot apps for anxiety and depression. Eligibility was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and post-installation by two reviewers. Information on quality was assessed by following the mHONcode principles. Results: Only a handful (n=11) of chatbots were included from an initial search of 1000 that provide a substitute for human-human based interaction and clearly had a therapeutic human substitute goal in mind. The majority of reviewed apps had a high number of downloads indicating their popularity. The apps were also of a general high quality based on our assessment according to the mHONcode principles. Conclusion: The general popularity of apps reviewed, and results of our quality assessment indicate chatbots have a promising future within the realm of anxiety and depression. Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed low-cost assistance to professionals. © 2021

关键词： ”Anxiety” ”Chatbots” ”COVID-19” ”Depression” ”Pandemics”

Non-alcoholic fatty liver disease is not independent risk factor for cardiovascular disease event:A cohort study

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World Journal of Hepatology 2020年第6期12卷 323-331页

作者： Nima Motamed Hossein Ajdarkosh Maral Ahmadi Dhayaneethie Perumal G Hossein Ashrafi Mehdi Nikkhah Amir Hossein Faraji Mansooreh Maadi Mahmoodreza Khoonsari Nader Rezaie Behzad Farahani Fahimeh Safarnezhad Tameshkel Mitra Ameli Mahshid Panahi Mohammad Hadi Karbalaie Niya Farhad Zamani Department of Social Medicine Zanjan University of Medical SciencesZanjan ***Iran Gastrointestinal and Liver Diseases Research Center Iran University of Medical SciencesTehran ***Iran Faculty of Science Engineering and ComputingKingston UniversityKingstonLondon KT12EEUnited Kingdom Cancer Theme SEC Faculty Penrhyn Road Kingston UniversityLondon KT12EEUnited Kingdom Department of Pulmonology Firouzgar HospitalIran University of Medical SciencesTehran ***Iran Department of Cardiology Iran University of Medical SciencesTehran ***Iran

BACKGROUND There are no consistent results between previous studies for an independent association between non-alcoholic fatty liver disease(NAFLD)and cardiovascular disease(CVD)*** To determine if there is an independent association between NAFLD and CVD *** In the present study,valid outcome data of 4808 subjects were available for phase 2 of our cohort *** subjects had been followed up for seven years from phase 1,beginning in 2009-2010 to phase 2 during *** and multiple Cox proportional models were used to determine the association between NAFLD in the primary phase of the cohort and subsequent fatal and non-fatal CVD events during *** The incidence of non-fatal CVD events in males with NAFLD was significantly higher(P=0.004)than in males without NAFLD.A positive association was demonstrated between NAFLD and non-fatal CVD events in males(Hazard ratio=1.606;95%CI:1.166-2.212;P=0.004)by the simple Cox proportional hazard model,but no independent association was detected between these in the multiple Cox *** No independent association was detected between NAFLD and *** is likely that diabetes mellitus and age may be the principle mediators in this regard.

关键词： Non-alcoholic fatty liver disease Cardiovascular disease Cohort Type 2 diabetes mellitus Risk factor Follow up

Microvasculature segmentation and inter-capillary area quantification of the deep vascular complex using transfer learning

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arXiv 2020年

作者： Lo, Julian Heisler, Morgan Vanzan, Vinicius Karst, Sonja Matovinovic, Ivana Zadro Loncaric, Sven Navajas, Eduardo V. Beg, Mirza Faisal Sarunic, Marinko V. School of Engineering Science Simon Fraser University Canada Department of Ophthalmology and Visual Sciences University of British Columbia Canada Department of Ophthalmology and Optometry Medical University of Vienna Austria Faculty of Electrical Engineering and Computing University of Zagreb Croatia

Purpose: Optical Coherence Tomography Angiography (OCT-A) permits visualization of the changes to the retinal circulation due to diabetic retinopathy (DR), a microvascular complication of diabetes. We demonstrate accurate segmentation of the vascular morphology for the superficial capillary plexus and deep vascular complex (SCP and DVC) using a convolutional neural network (CNN) for quantitative analysis. Methods: Retinal OCT-A with a 6x6mm field of view (FOV) were acquired using a Zeiss PlexElite. Multiple-volume acquisition and averaging enhanced the vessel network contrast used for training the CNN. We used transfer learning from a CNN trained on 76 images from smaller FOVs of the SCP acquired using different OCT systems. Quantitative analysis of perfusion was performed on the automated vessel segmentations in representative patients with DR. Results: The automated segmentations of the OCT-A images maintained the hierarchical branching and lobular morphologies of the SCP and DVC, respectively. The network segmented the SCP with an accuracy of 0.8599, and a Dice index of 0.8618. For the DVC, the accuracy was 0.7986, and the Dice index was 0.8139. The inter-rater comparisons for the SCP had an accuracy and Dice index of 0.8300 and 0.6700, respectively, and 0.6874 and 0.7416 for the DVC. Conclusions: Transfer learning reduces the amount of manually-annotated images required, while producing high quality automatic segmentations of the SCP and DVC. Using high quality training data preserves the characteristic appearance of the capillary networks in each layer. Translational Relevance: Accurate retinal microvasculature segmentation with the CNN results in improved perfusion analysis in diabetic retinopathy. Copyright © 2020, The Authors. All rights reserved.

关键词： Eye protection

Correction to: Towards employing native information in citation function classification

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Scientometrics 2022年第11期127卷 6579-6579页

作者： Zhang, Yang Zhao, Rongying Wang, Yufei Chen, Haihua Mahmood, Adnan Zaib, Munazza Zhang, Wei Emma Sheng, Quan Z. School of Information Management Wuhan University Wuhan People’s Republic of China School of Computing Faculty of Science and Engineering Macquarie University Sydney Australia Department of Information Science University of North Texas Denton USA School of Computer Science The University of Adelaide Adelaide Australia

From Nano to Macro: Overview of the IEEE Bio Image and Signal Processing Technical Committee

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arXiv 2022年

作者： Aviyente, Selin Frangi, Alejandro Meijering, Erik Muñoz-Barrutia, Arrate Liebling, Michael De Ville, Dimitri Van Olivo-Marin, Jean-Christophe Kovačević, Jelena Unser, Michael The Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States Schools of Computing and Medicine University of Leeds LeedsLS2 9JT United Kingdom The Alan Turing Institute London United Kingdom and Cardiovascular Sciences KU Leuven Leuven Belgium The School of Computer Science and Engineering University of New South Wales SydneyNSW2052 Australia The Bioengineering Department Universidad Carlos III de Madrid Madrid Leganés Spain The Idiap Research Institute Martigny Switzerland The Neuro-X Institute School of Engineering EPFL Geneva Faculty of Medicine University of Geneva Switzerland The Cell Biology and Infection Department Institut Pasteur Paris France The New York University Tandon School of Engineering BrooklynNY United States The School of Engineering EPFL Lausanne Switzerland

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological imaging, digital pathology, molecular imaging, microscopy, and associated computational imaging, image analysis, and image-guided treatment, alongside physiological signal processing, computational biology, and bioinformatics. BISP has 40 members and covers a wide range of EDICS, including CIS-MI: Medical Imaging, BIO-MIA: Medical Image Analysis, BIO-BI: Biological Imaging, BIO: Biomedical Signal Processing, BIO-BCI: Brain/Human-Computer Interfaces, and BIO-INFR: Bioinformatics. BISP plays a central role in the organization of the IEEE International Symposium on Biomedical Imaging (ISBI) and contributes to the technical sessions at the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), and the IEEE International Conference on Image Processing (ICIP). In this paper, we provide a brief history of the TC, review the technological and methodological contributions its community delivered, and highlight promising new directions we anticipate. © 2022, CC BY.

关键词： Bioinformatics

Application of ChatGPT in multilingual medical education: How does ChatGPT fare in 2023's Iranian residency entrance examination

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Informatics in Medicine Unlocked 2023年 41卷

作者： Khorshidi, Hamid Mohammadi, Afshin Yousem, David M. Abolghasemi, Jamileh Ansari, Golnoosh Mirza-Aghazadeh-Attari, Mohammad Acharya, U Rajendra Abbasian Ardakani, Ali Department of Information Engineering University of Padova Padova Italy Department of Radiology Faculty of Medicine Urmia University of Medical Science Urmia Iran Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins Medical Institutions Baltimore MD United States Department of Biostatistics School of Public Health Iran University of Medical Sciences Tehran Iran Department of Radiology Northwestern University Feinberg School of Medicine 420 E Superior St Chicago IL United States School of Mathematics Physics and Computing University of Southern Queensland Springfield QLD Australia Department of Radiology Technology School of Allied Medical Sciences Shahid Beheshti University of Medical Sciences Tehran Iran

Background: ChatGPT is a large language model (LLM) artificial intelligence instrument trained on massive amounts of text data extracted from the internet and/or user input. In the present article, we aim to apply the latest version of ChatGPT to the Iranian Medical Residency Examination. Methods: The Iranian Medical Residency Examination is composed of 200 multichoice questions covering all domains of medicine. We used ChatGPT to translate questions into English, French, and Spanish. We fed the questions as multiple-choice questions and allowed ChatGPT to provide comprehensive answers and justifications for its choices. Results: ChatGPT was able to answer 161 (81.3% = 161/198) questions correctly when the Persian language was used. When the questions were translated into English, French, and Spanish, ChatGPT answered six, one, and five additional questions correctly, respectively. When comparing the different languages, there was no significant difference in the functioning of ChatGPT in different languages using either the McNemar test or the Binomial test. Conclusion: ChatGPT can deliver above-average performance in the Iranian Medical Residency Examination, demonstrating its potential for using language models in medicine. © 2023 The Authors

关键词： ChatGPT Language model Medical education USMLE

Multimodal Segmentation Neural Network to Determine the Cause of Damage to Grasslands

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Multimodal Segmentation Neural Network to Determine the Caus...

International Conference on Software, Telecommunications and Computer Networks (SoftCOM)

作者： Maximilian Johenneken Ahmad Drak Rainer Herpers Alexander Asteroth Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany Institute of Visual Computing Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany University College London London United Kingdom Faculty of Computer Science University of New Brunswick Fredericton Canada Lassonde School of Engineering York University Toronto Canada

Agricultural fields suffer from damage due to changing climate conditions and wildlife foraging. Damage incurred by wild boar is classified as the main contributing factor to grasslands damage. Such damage results in losses for farmers due to reduced yield potential and repair costs. The extent of wild boar damage is typically estimated manually by using ground based approaches (e.g. GPS measurements), which is a time consuming task with questionable accuracy. Building upon our previous work, we present an autonomous approach to detect and classify the cause of damage to grasslands (wild boar, mole etc.). The approach entails utilizing convolutional neural networks for semantic segmentation of grasslands. An RGB baseline was established, in addition to evaluating multimodal architectures that incorporate different surface model feature representations, leading to a joint representation of spectral and elevation information. Testing and experimentation was performed in real-world grasslands around Bonn, Germany. The results show that incorporating elevation features with late fusion enhances the overall performance of the network over the RGB baselines.

关键词： Wildlife Semantics Neural networks Time measurement Software Telecommunications Sensors

Conflict-free collective stochastic decision making by orbital angular momentum of photons through quantum interference

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arXiv 2021年

作者： Amakasu, Takashi Chauvet, Nicolas Bachelier, Guillaume Huant, Serge Horisaki, Ryoichi Naruse, Makoto Department of Mathematical Engineering and Information Physics Faculty of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Université Grenoble Alpes CNRS Institut Néel Grenoble38042 France

In recent cross-disciplinary studies involving both optics and computing, single-photon-based decision-making has been demonstrated by utilizing the wave-particle duality of light to solve multi-armed bandit problems. Furthermore, entangled-photon-based decision-making has managed to solve a competitive multi-armed bandit problem in such a way that conflicts of decisions among players are avoided while ensuring equality. However, as these studies are based on the polarization of light, the number of available choices is limited to two, corresponding to two orthogonal polarization states. Here we propose a scalable principle to solve competitive decision-making situations by using the orbital angular momentum of photons based on its high dimensionality, which theoretically allows an unlimited number of arms. Moreover, by extending the Hong-Ou-Mandel effect to more than two states, we theoretically establish an experimental configuration able to generate multi-photon states with orbital angular momentum and conditions that provide conflict-free selections at every turn. We numerically examine total rewards regarding three-armed bandit problems, for which the proposed strategy accomplishes almost the theoretical maximum, which is greater than a conventional mixed strategy intending to realize Nash equilibrium. This is thanks to the quantum interference effect that achieves no-conflict selections, even in the exploring phase to find the best arms. © 2021, CC BY.

关键词： Photons

Applications of Explainable AI for 6G: Technical Aspects, Use Cases, and Research Challenges

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arXiv 2021年

作者： Wang, Shen Qureshi, M. Atif Miralles-Pechuán, Luis Huynh-The, Thien Gadekallu, Thippa Reddy Liyanage, Madhusanka The School of Computer Science University College Dublin Ireland ADAPT Centre eXplainable Analytics Group Faculty of Business Technological University Dublin Ireland The School of Computing Technological University Dublin Central Quad Grangegorman Dublin Ireland The Department of Computer and Communication Engineering Ho Chi Minh City University of Technology and Education Viet Nam The School of Information Technology and Engineering Vellore Institute of Technology India The Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

When 5G began its commercialisation journey around 2020, the discussion on the vision of 6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability, energy efficiency, lower latency, and an integrated "human-centric" network system powered by artificial intelligence (AI). Such a 6G network will lead to an excessive number of automated decisions made in real-time. These decisions can range widely, from network resource allocation to collision avoidance for self-driving cars. However, the risk of losing control over decision-making may increase due to high-speed, data-intensive AI decision-making beyond designers' and users' comprehension. The promising explainable AI (XAI) methods can mitigate such risks by enhancing the transparency of the black box AI decision-making process. This paper surveys the application of XAI towards the upcoming 6G age in every aspect, including 6G technologies (e.g., intelligent radio, zero-touch network management) and 6G use cases (e.g., industry 5.0). Moreover, we summarised the lessons learned from the recent attempts and outlined important research challenges in applying XAI for 6G in the near future. Copyright © 2021, The Authors. All rights reserved.

关键词： Decision making