Article
Health Care Sciences & Services
Varun Suraj, Catherine Del Vecchio Fitz, Laura B. Kleiman, Suresh K. Bhavnani, Chinmay Jani, Surbhi Shah, Rana R. McKay, Jeremy Warner, Gil Alterovitz
Summary: This paper describes the creation of the SMART COVID Navigator, a clinical decision support tool designed to assist physicians in treating COVID-19 patients. The tool connects electronic health records with data from observational studies to predict the fatality and severity of COVID-19 progression based on a patient's medical conditions, allowing physicians to determine appropriate treatment strategies.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Rita Murri, Carlotta Masciocchi, Jacopo Lenkowicz, Massimo Fantoni, Andrea Damiani, Antonio Marchetti, Paolo Domenico Angelo Sergi, Giovanni Arcuri, Alfredo Cesario, Stefano Patarnello, Massimo Antonelli, Rocco Bellantone, Roberto Bernabei, Stefania Boccia, Paolo Calabresi, Andrea Cambieri, Roberto Cauda, Cesare Colosimo, Filippo Crea, Ruggero De Maria, Valerio De Stefano, Francesco Franceschi, Antonio Gasbarrini, Raffaele Landolfi, Ornella Parolini, Luca Richeldi, Maurizio Sanguinetti, Andrea Urbani, Maurizio Zega, Giovanni Scambia, Vincenzo Valentini
Summary: This study describes an AI-based COVID-19 data management system that utilizes real-time, centralized, and standardized patient data to improve COVID-19 patient management and clinical outcomes. The system includes a large collection of clinical data and a real-time updated dashboard to support COVID-19 patient management at different levels and promote disease prediction research. This approach has great potential for application in similar situations.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Immunology
Caitlin M. Dugdale, David M. Rubins, Hang Lee, Suzanne M. McCluskey, Edward T. Ryan, Camille N. Kotton, Rocio M. Hurtado, Andrea L. Ciaranello, Miriam B. Barshak, Dustin S. McEvoy, Sandra B. Nelson, Nesli Basgoz, Jacob E. Lazarus, Louise C. Ivers, Jennifer L. Reedy, Kristen M. Hysell, Jacob E. Lemieux, Howard M. Heller, Sayon Dutta, John S. Albin, Tyler S. Brown, Amy L. Miller, Stephen B. Calderwood, Rochelle P. Walensky, Kimon C. Zachary, David C. Hooper, Emily P. Hyle, Erica S. Shenoy
Summary: The use of the CORAL system for evaluating PUIs can reduce repeated testing, shorten the time for PUI status discontinuation, and decrease infectious diseases physician work hours, making it an efficient and effective diagnostic method.
CLINICAL INFECTIOUS DISEASES
(2021)
Article
Computer Science, Interdisciplinary Applications
Andreas Tolk, Christopher Glazner, Joseph Ungerleider
Summary: The COVID-19 Healthcare Coalition was established to respond to the pandemic by bringing together various stakeholders to protect the healthcare system and provide real-time data-driven insights. To achieve this, the coalition utilized a combination of machine learning algorithms and theory-based simulations for computational decision support.
COMPUTING IN SCIENCE & ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Muhammad Sajjad Ali Khan, Saeed Ullah Jan, Rahim Jan, Tapan Senapati, Sarbast Moslem
Summary: This paper focuses on the study of new operators for complex interval-valued intuitionistic fuzzy sets based on Aczel-Alsina t-norm and t-conorm. The operators developed include complex interval-valued intuitionistic Aczel-Alsina weighted average, complex interval-valued intuitionistic Aczel-Alsina weighted geometric, complex interval-valued intuitionistic Aczel-Alsina ordered weighted average, and complex interval-valued intuitionistic Aczel-Alsina ordered weighted geometric. These operators are more adaptable and give more accurate results than existing ones. A group decision-making method and a multi-criteria decision-making technique are also developed based on the proposed operators.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Lakshita Aggarwal, Puneet Goswami, Shelly Sachdeva
Summary: COVID-19 has become a global concern, highlighting the need to strengthen early warning systems and risk management. A decision support system based on machine learning algorithms is proposed, and an additive utility assumption approach is validated for a multi-criterion intelligent decision support system through empirical analysis.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Electrical & Electronic
Summrina Kanwal, Faiza Khan, Sultan Alamri, Kia Dashtipur, Mandar Gogate
Summary: The coronavirus pandemic has had a significant impact on global public health. The use of artificial intelligence and machine learning techniques for the detection of COVID-19 infection has become crucial in containing the spread of the disease. The proposed hybrid approach of combining optimized artificial immune networks algorithm with deep learning and machine learning techniques has shown improved accuracy in disease prediction.
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
(2022)
Article
Public, Environmental & Occupational Health
Lina Diaz-Castro, Jose Carlos Suarez-Herrera, Oscar Omar Gonzalez-Ruiz, Emanuel Orozco-Nunez, Mario Salvador Sanchez-Dominguez
Summary: This research aims to analyze the governance processes in the formulation of healthcare policies for people with mental disorders during the COVID-19 pandemic. The findings revealed a lack of specific policies and measures to address the needs of this vulnerable population in Mexico, and highlighted the importance of considering the role and influence of different actors in the decision-making process.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Public, Environmental & Occupational Health
Alice Roebbelen, Malte L. Schmieding, Marvin Kopka, Felix Balzer, Markus A. Feufel
Summary: This study compares the effectiveness of interactive decision support tools (DSTs) and static flowcharts in providing decision support. The findings suggest that static flowcharts can be equally beneficial as interactive tools, especially when the decision space is limited. Static flowcharts are more transparent and cost-effective, making them more efficient in guiding the public. Further research is needed to validate these findings and explore the trade-off between transparency and convenience in DSTs, as well as the suitability of different user interfaces for specific user groups.
JMIR PUBLIC HEALTH AND SURVEILLANCE
(2022)
Article
Nursing
Grant A. Pignatiello, Emily Tsivitse, Julia O'Brien, Noa Kraus, Ronald L. Hickman
Summary: This study confirmed the validity and reliability of the Decision Fatigue Scale (DFS) in assessing decision fatigue among clinical nurses, providing a reliable instrument to measure the burden of decision-making in this population.
JOURNAL OF CLINICAL NURSING
(2022)
Article
Public, Environmental & Occupational Health
Shazia Rehman, Erum Rehman, Jianglin Zhang
Summary: This study investigated the influence of decision regret and post-vaccination adverse effects on the inclination to receive booster shots. The findings revealed that healthcare workers with unfavorable vaccination responses were more likely to regret their prior immunization decisions, which in turn affected their decision to get booster shots.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Computer Science, Information Systems
Alan H. Morris, Christopher Horvat, Brian Stagg, David W. Grainger, Michael Lanspa, James Orme, Terry P. Clemmer, Lindell K. Weaver, Frank O. Thomas, Colin K. Grissom, Ellie Hirshberg, Thomas D. East, Carrie Jane Wallace, Michael P. Young, Dean F. Sittig, Mary Suchyta, James E. Pearl, Antinio Pesenti, Michela Bombino, Eduardo Beck, Katherine A. Sward, Charlene Weir, Shobha Phansalkar, Gordon R. Bernard, B. Taylor Thompson, Roy Brower, Jonathon Truwit, Jay Steingrub, R. Duncan Hiten, Douglas F. Willson, Jerry J. Zimmerman, Vinay Nadkarni, Adrienne G. Randolph, Martha A. Q. Curley, Christopher J. L. Newth, Jacques Lacroix, Michael S. D. Agus, Kang Hoe Lee, Bennett P. DeBoisblanc, Frederick Alan Moore, R. Scott Evans, Dean K. Sorenson, Anthony Wong, Michael Boland, Willard H. Dere, Alan Crandall, Julio Facelli, Stanley M. Huff, Peter J. Haug, Ulrike Pielmeier, Stephen E. Rees, Dan S. Karbing, Steen Andreassen, Eddy Fan, Roberta M. Goldring, Kenneth Berger, Beno W. Oppenheimer, E. Wesley Ely, Brian W. Pickering, David A. Schoenfeld, Irena Tocino, Russell S. Gonnering, Peter J. Pronovost, Lucy A. Savitz, Didier Dreyfuss, Arthur S. Slutsky, James D. Crapo, Michael R. Pinsky, Brent James, Donald M. Berwick
Summary: Delivering the best care in various clinical settings is a challenging problem. Evidence-based guidelines currently address only a fraction of the care provided by clinicians, especially in underserved areas. The use of validated clinical decision support systems (eActions) could help overcome cognitive limitations in advanced healthcare environments.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2022)
Article
Immunology
Miloslav Klugar, Abanoub Riad, Lekshmi Mohanan, Andrea Pokorna
Summary: A survey in Czech healthcare workers revealed that a high percentage were willing to accept COVID-19 vaccine booster doses, with medical professionals, males, and older participants more likely to accept them. Perceived effectiveness against severe illness, symptomatic infection, and community transmission was a significant predictor for acceptance, while safety and ethical considerations should be addressed when communicating with healthcare workers.
Article
Health Care Sciences & Services
Gema Castillo-Sanchez, Olga Sacristan-Martin, Maria A. Hernandez, Irene Munoz, Isabel de la Torre, Manuel Franco-Martin
Summary: During the first COVID-19 lockdown in Spain, an online mindfulness course was implemented to support the mental health of healthcare professionals. The majority of participants expressed high satisfaction with the course and expressed willingness to participate again. The course had a good participation rate among female nurses.
JOURNAL OF MEDICAL SYSTEMS
(2022)
Article
Infectious Diseases
Antonio Ieni, Giovanni Tuccari
Summary: Pathologists collaborate with clinical infectious disease teams in diagnostic steps for COVID-19 patients, utilizing cytological and histopathological procedures to understand the disease's pathobiology. They have also introduced guidelines for high biosafety levels to prevent virus diffusion during the pandemic.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2021)
Article
Critical Care Medicine
Giorgia Carra, Fabian Guiza, Ian Piper, Giuseppe Citerio, Andrew Maas, Bart Depreitere, Geert Meyfroidt
Summary: Treatment and prevention of elevated intracranial pressure (ICP) is crucial in patients with severe traumatic brain injury (TBI). Prediction of harmful episodes of ICP dose could allow for a more proactive and preventive management of TBI, with potential implications on patients' outcomes.
JOURNAL OF NEUROTRAUMA
(2023)
Letter
Critical Care Medicine
Ari Ercole
INTENSIVE CARE MEDICINE
(2023)
Article
Critical Care Medicine
Lennart Riemann, Ana Mikolic, Andrew Maas, Andreas Unterberg, Alexander Younsi
Summary: We investigated the relationship between the presence of intracranial traumatic CT pathologies and the global functional outcome one year after mTBI in young patients. The study included all patients with mTBI (GCS: 13-15) aged <=24 years from the CENTER-TBI study. The results showed that patients with CT abnormalities were less likely to achieve complete recovery 12 months post-injury.
JOURNAL OF NEUROTRAUMA
(2023)
Article
Biochemical Research Methods
Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolo Pancino, Pietro Lio
Summary: Drug side-effects have a significant impact on public health, care system costs, and drug discovery processes. Predicting the probability of side-effects before their occurrence is crucial to reduce this impact, especially in drug discovery. By integrating heterogeneous data into a graph dataset, this study successfully utilizes Graph Neural Networks (GNNs) to predict drug side-effects, showing promising results. The experimental results highlight the significance of utilizing relationships between data entities and suggest potential future developments in this field.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Anesthesiology
Erta Beqiri, Ari Ercole, Marcel J. H. Aries, Michal Placek, Jeanette Tas, Marek Czosnyka, Nino A. Stocchetti, Peter Smielewski
Summary: The purpose of this study was to increase the stability and reliability of the CPPopt automated algorithm and validate the adjusted algorithm in a multi-center TBI cohort. The fine-tuned algorithm showed improved stability and maintained prognostic power for predicting mortality within 6 months.
JOURNAL OF CLINICAL MONITORING AND COMPUTING
(2023)
Article
Medicine, General & Internal
Razvan Bologheanu, Lorenz Kapral, Daniel Laxar, Mathias Maleczek, Christoph Dibiasi, Sebastian Zeiner, Asan Agibetov, Ari Ercole, Patrick Thoral, Paul Elbers, Clemens Heitzinger, Oliver Kimberger
Summary: Using reinforcement learning, researchers found that individualized use of corticosteroids in sepsis may lead to a mortality benefit, and the optimal treatment policy may be more restrictive than routine clinical practice.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Health Care Sciences & Services
Ari Ercole, Claire Tolliday, William Gelson, James H. F. Rudd, Ewen Cameron, Afzal Chaudhry, Fiona Hamer, Justin Davies
Summary: This study introduced a secure messaging system to replace outdated bleep/long-range pager equipment in the NHS. After months of socialization, the system was successfully implemented with high engagement and a significant decrease in internal call activity. The majority of users were satisfied with using personal devices for messaging after reassurance about privacy.
BMJ HEALTH & CARE INFORMATICS
(2023)
Article
Computer Science, Information Systems
Nuruzzaman Faruqui, Mohammad Abu Yousuf, Md Whaiduzzaman, A. K. M. Azad, Salem A. Alyami, Pietro Lio, Muhammad Ashad Kabir, Mohammad Ali Moni
Summary: The Internet of Medical Things (IoMT) has become an attractive target for cybercriminals due to its market value and rapid growth. However, IoMT devices have limited computational capabilities, making them vulnerable to cyber-attacks. To address this, a novel Intrusion Detection System (IDS) called SafetyMed is proposed, which combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to defend against intrusion from sequential and grid data. SafetyMed has shown high detection rates and accuracy, making it a potential game-changer in vulnerable sectors like the medical industry.
Article
Physics, Multidisciplinary
Casey Adam, Celine Kayal, Ari Ercole, Sonia Contera, Hua Ye, Antoine Jerusalem
Summary: This study demonstrates that general anaesthetics affect the viscoelasticity and functional activity of cells simultaneously, and that the alterations in firing and viscoelasticity are correlated.
COMMUNICATIONS PHYSICS
(2023)
Article
Health Care Sciences & Services
Shubhayu Bhattacharyay, Pier Francesco Caruso, Cecilia Akerlund, Lindsay D. Wilson, Robert K. Stevens, David W. Menon, Ewout W. Steyerberg, David Nelson, Ari Ercole, CENTER TBI Investigators Participants
Summary: Existing methods to characterise the evolving condition of traumatic brain injury (TBI) patients in the intensive care unit (ICU) do not capture the necessary context for individualising treatment. In this study, the integration of heterogenous data from medical records was used to model the individualised impact of clinical course on 6-month functional outcome. The study showed that static variables accounted for the majority of functional outcome explanation after TBI.
NPJ DIGITAL MEDICINE
(2023)
Article
Critical Care Medicine
Erta Beqiri, Frederick Zeiler, Ari Ercole, Michal Placek, Jeanette Tas, Joseph Donnelly, Marcel J. H. Aries, Peter Hutchinson, David Menon, Nino Stocchetti, Marek Czosnyka, Peter Smielewski
Summary: A previous study suggested that the percentage of time spent with CPP below LLR is associated with mortality in TBI patients. This study aims to validate this finding in a large multicentre cohort.
Article
Health Care Sciences & Services
Md. Martuza Ahamad, Sakifa Aktar, Md. Jamal Uddin, Md. Rashed-Al-Mahfuz, A. K. M. Azad, Shahadat Uddin, Salem A. Alyami, Iqbal H. Sarker, Asaduzzaman Khan, Pietro Lio, Julian M. W. Quinn, Mohammad Ali Moni
Summary: Good vaccine safety and reliability are crucial for countering infectious diseases effectively. This study aims to reduce adverse reactions to COVID-19 vaccines by identifying common factors through patient data analysis and classification. Patient medical histories and postvaccination effects were examined, and statistical and machine learning approaches were used. The analysis revealed that prior illnesses, hospital admissions, and SARS-CoV-2 reinfection were significantly associated with poor patient reactions.
Article
Critical Care Medicine
Lennart Riemann, Ana Mikolic, Andrew Maas, Andreas Unterberg, Alexander Younsi
Summary: The study investigated the relationship between traumatic intracranial computed tomography (CT) pathologies and global functional outcome in young patients one year after mild traumatic brain injury (mTBI). It found that the presence of intracranial traumatic CT pathologies was predictive of outcome 12 months after mTBI in young patients.
JOURNAL OF NEUROTRAUMA
(2023)
Letter
Critical Care Medicine
Erta Beqiri, Joseph Donnelly, Marcel Aries, Ari Ercole, Peter Smielewski
Article
Critical Care Medicine
Agnieszka Kazimierska, Agnieszka Uryga, Cyprian Mataczynski, Marek Czosnyka, Erhard W. Lang, Magdalena Kasprowicz
Summary: This study investigates the relationship between intracranial pressure pulse shape and CT features in traumatic brain injury patients. The results reveal that pulse shape index is associated with intracranial mass lesions (including midline shift and space-occupying lesions) and correlates significantly with the extent of the lesions and CT scores.