Review
Psychiatry
Nicolas Tajan, Maud Deves, Remy Potier
Summary: The COVID-19 pandemic has caused a significant shift in psychotherapy practices, with a focus on teletherapy and online consultations. This review aimed to identify the challenges faced by psychotherapists in adopting these new methods, and it contributes to the evaluation of tele mental health services.
FRONTIERS IN PSYCHIATRY
(2023)
Article
Health Care Sciences & Services
Andy Wong, Rashaad Bhyat, Siddhartha Srivastava, Lysa Boisse Lomax, Ramana Appireddy
Summary: Virtual care, utilizing videoconferencing technology, is crucial during the current COVID-19 pandemic to provide ongoing care for patients. Health care providers need to understand the nuances of virtual care, including regulatory standards, technology, patient selection, and workflow, to deliver high-quality, equitable, and professional care. This will inspire patient trust and ensure seamless transitions between in-person and virtual care.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Review
Health Care Sciences & Services
Christian Rauschenberg, Anita Schick, Dusan Hirjak, Andreas Seidler, Isabell Paetzold, Christian Apfelbacher, Steffi G. Riedel-Heller, Ulrich Reininghaus
Summary: This study reviewed the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health. The findings suggest good evidence on eHealth interventions and promising evidence on mHealth apps, with limited evidence on long-term effects and cost-effectiveness. Digital interventions are seen as particularly well-suited for mitigating psychosocial consequences at the population level during times of physical distancing and social restrictions.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Critical Care Medicine
Traci N. Adams, Rosechelle M. Ruggiero, Carol S. North
Summary: Frontline workers faced extreme stress levels during the COVID-19 pandemic, and supporting their emotional and mental health needs is crucial. This article proposes strategies that integrate knowledge from disaster mental health literature and lessons learned during the pandemic to address the needs of frontline healthcare workers. The strategies include distinguishing psychiatric illness from normative distress, providing treatment for psychopathologic symptoms, and offering supportive care interventions for frontline workers' emotional distress.
Article
Psychiatry
Mahsa Kamali, Marzieh Azizi, Mahmood Moosazadeh, Hossein Mehravaran, Roya Ghasemian, Maryam Hasannezhad Reskati, Forouzan Elyasi
Summary: This study investigated the prevalence rate of occupational burnout among healthcare workers in Iran during the COVID-19 pandemic. The findings showed a high prevalence rate of 18.3% and suggested that attention and intervention should be focused on improving the mental health of these individuals.
Article
Health Care Sciences & Services
Ellie Yu, Bowen Xu, Lydia Sequeira
Summary: This study aimed to identify factors associated with the utilization of e-Mental health (eMH) services across Canada during the COVID-19 pandemic. The results showed that users of eMH services were more likely to have regular family physician access, live in nonrural communities, have higher education levels, and be eHealth literate. Those with lower eMH usage were less likely to speak English at home. These findings highlight the importance of tailoring digital interventions to users of eMH services and raising awareness among nonusers.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Letter
Medicine, General & Internal
Reza Rastmanesh
Summary: This letter suggests conducting a sex subgroup analysis to determine if Covid-19 vaccines have the same effect on reducing viral shedding in men and women.
NEW ENGLAND JOURNAL OF MEDICINE
(2022)
Article
Health Care Sciences & Services
Malin Lohela-Karlsson, Emelie Conden Mellgren
Summary: This study compared the health consequences among Swedish healthcare workers involved in the care of COVID-19 patients. The results showed that HCWs directly involved in COVID-19 care experienced poorer sleep quality and higher levels of emotional and physical exhaustion. There were no significant differences in health consequences among different occupational groups involved in COVID-19 care.
Article
Public, Environmental & Occupational Health
Zineb El Otmani Dehbi, Hayat Sedrati, Souad Chaqsare, Abdellah Idrissi Azami, Mohamed Merzouki, Mourad Raji, Wajih Rhalem, Najib Al Idrissi, Chakib Nejjari, Saaid Amzazi, Hassan Ghazal
Summary: Morocco has made significant progress in digital health, extensively deploying digital technology to support the management of the current health crisis. The successful implementation of various digital health strategies has positioned Morocco as a key player in achieving Sustainable Development Goals, showcasing the effectiveness of digitalization in managing health aspects of the pandemic and future health system development in the African continent.
FRONTIERS IN PUBLIC HEALTH
(2021)
Review
Public, Environmental & Occupational Health
Leonard Baatiema, Olutobi A. Sanuade, Luke N. Allen, Seye Abimbola, Celestin Hategeka, Kwadwo A. Koram, Margaret E. Kruk
Summary: During the COVID-19 pandemic, health care access for people with non-communicable diseases (NCDs) has been disrupted, leading to the need for health system adaptations and innovative service delivery models. Through our research, we identified and summarized several adaptations and interventions, such as telemedicine, medicine drop-off points, decentralized follow-up services, and smartphone-based retinal camera screening, which have improved access to NCD care and eased the burden on patients.
JOURNAL OF GLOBAL HEALTH
(2023)
Letter
Medicine, General & Internal
Sharon Amit, Tal Gonen, Gili Regev-Yochay
Summary: A study found that breakthrough infections among fully vaccinated healthcare workers are limited, with no evidence of secondary transmission in most cases. Despite some breakthrough infections, the proportion of such cases is relatively low among fully vaccinated healthcare workers.
NEW ENGLAND JOURNAL OF MEDICINE
(2021)
Article
Health Care Sciences & Services
Maga Jackson-Triche, Don Vetal, Eva -Marie Turner, Priya Dahiya, Christina Mangurian
Summary: During the COVID-19 pandemic, a chatbot program was implemented at a large academic medical center to provide behavioral health assessment and treatment for the workforce. The chatbot successfully guided employees to appropriate services based on their needs. This technology has the potential to be scaled and used in other medical settings.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Review
Psychology, Multidisciplinary
Ping Sun, Manli Wang, Tingting Song, Yan Wu, Jinglu Luo, Lili Chen, Lei Yan
Summary: The COVID-19 pandemic has caused significant psychological impact on healthcare workers, particularly among women and frontline workers, leading to high prevalence of anxiety, depression, and insomnia. Timely psychological counseling and intervention are crucial to alleviate their anxiety and improve their overall mental health.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Public, Environmental & Occupational Health
Joseph Ollier, Simon Neff, Christine Dworschak, Arber Sejdiji, Prabhakaran Santhanam, Roman Keller, Grace Xiao, Alina Asisof, Dominik Ruegger, Caterina Berube, Lena Hilfiker Tomas, Joel Neff, Jiali Yao, Aishah Alattas, Veronica Varela-Mato, Amanda Pitkethly, Ma Dolores Vara, Rocio Herrero, Rosa Ma Banos, Carolina Parada, Rajashree Sundaram Agatheswaran, Victor Villalobos, Olivia Clare Keller, Wai Sze Chan, Varun Mishra, Nicholas Jacobson, Catherine Stanger, Xinming He, Viktor von Wyl, Steffi Weidt, Severin Haug, Michael Schaub, Birgit Kleim, Jurgen Barth, Claudia Witt, Urte Scholz, Elgar Fleisch, Florian von Wangenheim, Lorainne Tudor Car, Falk Mueller-Riemenschneider, Sandra Hauser-Ulrich, Alejandra Nunez Asomoza, Alicia Salamanca-Sanabria, Jacqueline Louise Mair, Tobias Kowatsch
Summary: Elena+ is a smartphone-based conversational agent designed to help individuals maintain healthy lifestyles during the COVID-19 pandemic, providing guidance on mental health, physical activity, sleep, diet, and nutrition.
FRONTIERS IN PUBLIC HEALTH
(2021)
Article
Public, Environmental & Occupational Health
Young E. Choi, Seung H. Lee, Yun J. Kim, Jeong G. Lee, Yu H. Yi, Young J. Tak, Gyu L. Kim, Young J. Ra, Sang Y. Lee, Young H. Cho, Eun J. Park, Young Lee, Jung Choi, Sae R. Lee, Ryuk J. Kwon, Soo M. Son, Yea J. Lee, Min J. Kang
Summary: This study aimed to compare the level of burnout among nurses in general wards and COVID-19-dedicated wards in a national university hospital, and identify the risk factors. The results showed that nurses in general wards had a higher emotional impairment score than those in COVID-19 wards, and were at a higher risk of presenting with total-core symptoms. Short career length and presence of an underlying disease were identified as risk factors for mental distance.
JOURNAL OF PUBLIC HEALTH
(2023)
Article
Health Care Sciences & Services
Nidal Drissi, Sofia Ouhbi, Mohamed Adel Serhani, Goncalo Marques, Isabel de la Torre Diez
Summary: This study presents a synthesis of global attitudes toward connected mental health (CMH) use and the use of technology in mental care. It found that the investigated cohorts generally had positive attitudes towards CMH use and had high levels of technology use and ownership. Preferred criteria for CMH use were identified, and concerns related to technology access, digital divide, and lack of knowledge and reservations towards CMH were addressed.
TELEMEDICINE AND E-HEALTH
(2023)
Article
Computer Science, Artificial Intelligence
Hafeez Ur Rehman Siddiqui, Beatriz Sainz de Abajo, Isabel de la Torre Diez, Furqan Rustam, Amjad Raza, Sajjad Atta, Imran Ashraf
Summary: Bankruptcy prediction is crucial in the accounting and finance field, and emotions extracted from earning calls can be used to train deep learning models for this purpose. The results show that the models using LSTM extracted features provide better performance in predicting bankruptcy and non-bankruptcy compared to traditional features.
PEERJ COMPUTER SCIENCE
(2023)
Article
Chemistry, Analytical
Sana Farooq, Ayesha Altaf, Faiza Iqbal, Ernesto Bautista Thompson, Debora Libertad Ramirez Vargas, Isabel de la Torre Diez, Imran Ashraf
Summary: Recent developments in quantum computing have raised concerns about the security of conventional public encryption systems. The National Institute of Standards and Technology (NIST) is actively seeking post-quantum encryption algorithms that can resist quantum computer attacks. This study evaluates the performance of two post-quantum cryptography algorithms and provides insights for researchers and practitioners in selecting appropriate algorithms.
Article
Virology
Jamal Bakkas, Mohamed Hanine, Abderrahman Chekry, Said Gounane, Isabel de la Torre Diez, Vivian Lipari, Nohora Milena Martinez Lopez, Imran Ashraf
Summary: Mutations in viruses allow for continuous evolution and adaptation, making it challenging for researchers to control pandemics such as COVID-19. Understanding the mutation mechanism can help in developing strategies to control its spread and anticipate future mutations.
Article
Chemistry, Analytical
Imran Shafi, Muhammad Sajad, Anum Fatima, Daniel Gavilanes Aray, Vivian Lipari, Isabel de la Torre Diez, Imran Ashraf
Summary: This paper presents an IoT-based automated healthcare diagnosis model that utilizes data augmentation, transfer learning, and deep learning techniques and does not require physical interaction between patients and physicians. The model employs AI and a user-friendly interface to indicate dental issues and treatment options, making it accessible to laypeople. The proposed method involves data acquisition, preprocessing, deep learning-based feature extraction, and classification using an unsupervised neural network. The proposed automated model achieved an accuracy of 98% using the AlexNet-SVM combination, demonstrating its effectiveness.
Article
Chemistry, Analytical
Urooj Akram, Wareesa Sharif, Mobeen Shahroz, Muhammad Faheem Mushtaq, Daniel Gavilanes Aray, Ernesto Bautista Thompson, Isabel de la Torre Diez, Sirojiddin Djuraev, Imran Ashraf
Summary: This study proposes an IoT threat protection system (IoTTPS) using an ensemble model RKSVM, which includes random forest (RF), K nearest neighbor (KNN), and support vector machine (SVM) model, to protect IoT networks from threats. The experimental phase uses various machine learning algorithms and datasets such as KDD cup 99, NSL-KDD, and CICIDS.
Review
Chemistry, Analytical
Arooj Khan, Imran Shafi, Sajid Gul Khawaja, Isabel de la Torre Diez, Miguel Angel Lopez Flores, Juan Castanedo Galvlan, Imran Ashraf
Summary: This paper provides a comprehensive study of the issues and challenges of adaptive filtering by comparing different variants of PSO and analyzing the performance by combining PSO with other optimization algorithms to achieve better convergence, accuracy, and adaptability.
Article
Chemistry, Analytical
J. V. Bibal Benifa, Channabasava Chola, Abdullah Y. Y. Muaad, Mohd Ammar Bin Hayat, Md Belal Bin Heyat, Rajat Mehrotra, Faijan Akhtar, Hany S. S. Hussein, Debora Libertad Ramirez Vargas, Angel Kuc Castilla, Isabel de la Torre Diez, Salabat Khan
Summary: A new AI-based approach using a deep learning model was proposed to identify people who violate face mask protocol in public places. The model achieved a promising detection accuracy of 99.0% for identifying violations and outperformed other DL models by a significant margin. It is lightweight, has a high confidence score of 99.0%, and can perform real-time detection at 41.72 FPS. This developed model can be useful for governments to enforce mask-wearing rules.
Article
Chemistry, Analytical
Hafeez Ur Rehman Siddiqui, Faizan Younas, Furqan Rustam, Emmanuel Soriano Flores, Julien Brito Ballester, Isabel de la Torre Diez, Sandra Dudley, Imran Ashraf
Summary: This study presents a cutting-edge approach to predicting cricket batsman strokes using computer vision and machine learning. By extracting video features and using various algorithms, including the random forest algorithm, the study achieves an outstanding accuracy of 99.77%. The results can help improve coaching techniques, enhance batsmen's performance in cricket, and ultimately improve the overall quality of the game.
Article
Computer Science, Information Systems
R. Sudheesh, Muhammad Mujahid, Furqan Rustam, Rahman Shafique, Venkata Chunduri, Monica Gracia Villar, Julien Brito Ballester, Isabel de la Torre Diez, Imran Ashraf
Summary: This study performs sentiment analysis and topic modeling on ChatGPT-based tweets to assess the success and shortcomings of the ChatGPT tool. The proposed BERT model achieves superior performance in sentiment analysis.
Review
Environmental Studies
Saad Mazhar Khan, Imran Shafi, Wasi Haider Butt, Isabel de la Torre Diez, Miguel Angel Lopez Flores, Juan Castanedo Galan, Imran Ashraf
Summary: This comprehensive assessment focuses on flood control, exploring different types of natural disasters, utilizing advanced technologies such as big data analysis and cloud computing, collecting real-time data through sensor networks, modeling flood scenarios through model-driven engineering, visualizing and analyzing spatial data through Geographic Information System (GIS), and applying machine learning and data analytics for predictive modeling and risk assessment in flood management.
Review
Environmental Studies
Saad Mazhar Khan, Imran Shafi, Wasi Haider Butt, Isabel de la Torre Diez, Miguel Angel Lopez Flores, Juan Castanedo Galvlan, Imran Ashraf
Summary: This article proposes a novel flood disaster management system using the full lifecycle disaster event model, which integrates existing flood protocols, languages, and patterns to enhance emergency preparedness and response. The proposed system improves emergency response by providing a comprehensive framework for flood management, including pre-disaster planning, real-time monitoring, and post-disaster evaluation.
Correction
Health Care Sciences & Services
Antonio Ferreras, Sandra Sumalla-Cano, Rosmeri Martinez-Licort, Inaki Elio, Kilian Tutusaus, Thomas Prola, Juan Luis Vidal-Mazon, Benjamin Sahelices, Isabel de la Torre Diez
JOURNAL OF MEDICAL SYSTEMS
(2023)
Article
Health Care Sciences & Services
Anum Fatima, Imran Shafi, Hammad Afzal, Khawar Mahmood, Isabel de la Torre Diez, Vivian Lipari, Julien Brito Ballester, Imran Ashraf
Summary: Automated dental imaging interpretation using artificial intelligence is a highly productive field of research. Although X-ray imaging systems have enabled the identification of dental diseases, the manual process of assessment is tedious and error-prone. To address this, researchers have proposed a lightweight Mask-RCNN model for periapical disease detection using advanced computer vision techniques and machine learning. The model achieved high accuracy in detecting and localizing periapical lesions, outperforming existing methods.
Proceedings Paper
Computer Science, Software Engineering
Ita Richardson, Bilal Ahmad, Shweta Premanandan, Owen Doody, Sarah Beecham, Sofia Ouhbi, Muneef Alsahmmari, Asa Cajander
Summary: By developing design patterns, the research team has helped software engineers create more usable healthcare software to meet the needs of older adults and individuals with intellectual and developmental disabilities. They have also identified overlapping requirements between these two groups.
2023 IEEE 31ST INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE WORKSHOPS, REW
(2023)
