Article
Management
Lisheng He, Pantelis P. Analytis, Sudeep Bhatia
Summary: This study conducted a large-scale comparison of 58 prominent models of risky choice, revealing that crowds of risky choice models perform better than individual models and provide a performance bound for assessing the historical accumulation of knowledge in the field. The results suggest that each model captures unique aspects of the decision process, and existing models offer complementary rather than competing accounts of behavior.
MANAGEMENT SCIENCE
(2022)
Article
Physics, Multidisciplinary
Pavlin Mavrodiev, Frank Schweitzer
Summary: The wisdom of crowds refers to the phenomenon where the average opinion of a group closely aligns with the true answer. This requires group diversity of opinions and a small collective error. Social influence and individual conviction play a role in shaping opinions within the group, with social influence sometimes improving and sometimes deteriorating the outcome.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
History & Philosophy Of Science
Justin Sytsma, Ryan Muldoon, Shaun Nichols
Summary: Through simulations, it is shown that belief in universalism leads to quicker convergence and higher total payoffs in coordination problems, while relativism has its own advantages such as maintaining diversity in certain cases.
Article
Multidisciplinary Sciences
Jennifer Allen, Antonio A. Arechar, Gordon Pennycook, David G. Rand
Summary: Research suggests that using politically balanced groups of laypeople to identify misinformation is a feasible approach. Factors such as cognitive reflection, political knowledge, and party preference are related to agreement with fact-checkers among the general public.
Article
Computer Science, Artificial Intelligence
Musarrat Hussain, Fahad Ahmed Satti, Syed Imran Ali, Jamil Hussain, Taqdir Ali, Hun-Sung Kim, Kun-Ho Yoon, TaeChoong Chung, Sungyoung Lee
Summary: This paper presents research work in the field of healthcare to achieve a comprehensive framework using state-of-the-art machine learning techniques to extract knowledge from structured and unstructured data and integrate it with expert knowledge. The technique proposed shows higher accuracy compared to other methods, laying the foundation for an accurate and evolvable knowledge base that greatly enhances decision-making in the healthcare domain.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Management
Dennis Coates, Petr Parshakov
Summary: Crowd-sourcing of information is popular in sports, but crowd-sourced transfer fees may be biased as predictors of true market fees. This affects their usefulness as proxies for unknown salary in academic research and their impact on negotiations between clubs and players.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Multidisciplinary Sciences
Jeremy Turiel, Delmiro Fernandez-Reyes, Tomaso Aste
Summary: The study found a significant relationship between the initial social media reaction to COVID-19 and observed mortality a month later in Italy, Spain, and the United States, with Italy showing the strongest association. The collective wisdom of the crowds during the early stages of the pandemic remarkably predicted mortality rates almost a month later, reflecting the severity of the pandemic in different regions.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Stefany Moreno-Gamez, Michael E. Hochberg, G. S. van Doorn
Summary: Bacteria release and sense autoinducers to engage in quorum sensing, which is not only a means to estimate population density, but also a way to collectively sense the environment. A computational model shows that this functionality arises from individuals improving their estimation accuracy by pooling imperfect estimates, similar to the concept of 'wisdom of the crowds' in decision theory. This model reconciles the dependence of quorum sensing on both population density and the environment and explains the regulation of private goods production.
NATURE COMMUNICATIONS
(2023)
Article
Business
Khaled Saleh Al-Omoush, Maria Orero-Blat, Domingo Ribeiro-Soriano
Summary: This study reveals the significant role of sense of community in harnessing the wisdom of the crowd and creating collaborative knowledge, as well as its impact on the perceived value of social media crowdsourcing in responding to the COVID-19 crisis.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Chemistry, Multidisciplinary
Maria S. Garcia-Gonzalez, Enrique Paniagua-Aris, Rodrigo Martinez-Bejar, Juan A. Lopez-Caballero, Alessandro Gasparetto
Summary: In the construction of knowledge bases, evaluating the quality of the entered knowledge is crucial. This study presents an AI-based method that utilizes the structure and contents of knowledge representation schemas to evaluate knowledge.
APPLIED SCIENCES-BASEL
(2023)
Article
Multidisciplinary Sciences
Damon Centola, Joshua Becker, Jingwen Zhang, Jaya Aysola, Douglas Guilbeault, Elaine Khoong
Summary: Errors in clinical decision-making are common, with 10 to 15% of decisions being inaccurate. Experimental research shows that structured information-sharing networks among clinicians can significantly improve diagnostic accuracy and treatment decisions, reducing errors.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Communication
Yan Bei, Jian Lian, Ren Ruqin, Janet Fulk, Emily Sidnam-Mauch, Peter Monge
Summary: Research has found that communication network centralization has a negative impact on crowd wisdom, while shared task experience positively predicts crowd wisdom performance. Additionally, shared task experience moderates the effect of communication network centralization.
COMMUNICATION RESEARCH
(2021)
Article
Automation & Control Systems
Ye Tian, Long Wang, Francesco Bullo
Summary: This paper explores the impact of social influence on collective wisdom using a learning model, providing a mathematical model and theoretical analysis to examine the conditions and factors for improving or undermining collective accuracy.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2023)
Article
Computer Science, Artificial Intelligence
Pavlin Mavrodiev, Frank Schweitzer
Summary: Research suggests that under social influence, the wisdom of crowds may not always result in the correct answer, as agents tend to adjust their opinions and converge to a collective opinion that is often further away from the truth.
SWARM INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Yili Fang, Pengpeng Chen, Tao Han
Summary: The resourcefulness of crowdsourcing can be utilized to effectively handle multi-phase tasks through the novel approach called Hint, which incorporates task design, worker coordination, and coordination strategy.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Environmental Sciences
Francesc X. Marin-Gomez, Jacobo Mendioroz-Pena, Miguel-Angel Mayer, Leonardo Mendez-Boo, Nuria Mora, Eduardo Hermosilla, Ermengol Coma, Josep-Maria Vilaseca, Angela Leis, Manolo Medina, Queralt Miro Catalina, Josep Vidal-Alaball
Summary: This study investigated the differential characteristics between nursing home and non-nursing home elderly populations during the SARS-CoV-2 outbreak. The results showed differences in the form of epidemic outbreak and risk factors between the institutionalised and non-institutionalised elderly. The institutionalised population had a twenty-fold increase in adjusted mortality rate and a three-week delay in peak incidence. Unlike the non-institutionalised group, obesity and age were not significantly associated with death risk among the institutionalised, while having dementia was shown to be a risk factor.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Public, Environmental & Occupational Health
Azza Shoaibi, Gowtham A. Rao, Erica A. Voss, Anna Ostropolets, Miguel Angel Mayer, Juan Manuel Ramirez-Anguita, Filip Maljkovic, Biljana Carevic, Scott Horban, Daniel R. Morales, Talita Duarte-Salles, Clement Fraboulet, Tanguy Le Carrour, Spiros Denaxas, Vaclav Papez, Luis H. John, Peter R. Rijneek, Evan Minty, Thamir M. Alshammari, Rupa Makadia, Clair Blacketer, Frank DeFalco, Anthony G. Sena, Marc A. Suchard, Daniel Prieto-Alhambra, Patrick B. Ryan
Summary: This study explored the pre-pandemic co-occurrence of thrombosis with thrombocytopenia (TWT) using multiple observational health data sources. The results showed significant heterogeneity in TWT incidence rates across data sources and by age, sex, and TWT phenotypes. TWT patients were typically older men with comorbidities, and arterial thrombotic events were the most common among the different thrombosis types.
Article
Oncology
Angela Leis, David Casadevall, Joan Albanell, Margarita Posso, Francesc Macia, Xavier Castells, Juan Manuel Ramirez-Anguita, Jordi Martinez Roldan, Laura Furlong, Ferran Sanz, Francesco Ronzano, Miguel A. Mayer
Summary: This study compared the prevalence of depression in patients before and after diagnosis of breast or colorectal cancer and found that mining free-text clinical notes can identify more patients with depression. Additionally, a higher number of patients receiving chemotherapy had depression.
Article
Medicine, General & Internal
Xintong Li, Edward Burn, Talita Duarte-Salles, Can Yin, Christian Reich, Antonella Delmestri, Katia Verhamme, Peter Rijnbeek, Marc A. Suchard, Kelly Li, Mees Mosseveld, Luis H. John, Miguel-Angel Mayer, Juan-Manuel Ramirez-Anguita, Catherine Cohet, Victoria Strauss, Daniel Prieto-Alhambra
Summary: In this multinational study, a 30% increased risk of thrombocytopenia was observed after the first dose of ChAdOx1-S vaccine, and a trend towards an increased risk of venous thrombosis with thrombocytopenia syndrome was seen with Ad26.COV2.S compared with BNT162b2.
BMJ-BRITISH MEDICAL JOURNAL
(2022)
Article
Computer Science, Information Systems
Isaias Juarez-Barojas, Ruben Posada-Gomez, Alejandro Alvarado-Lassman, Jose Pastor Rodriguez-Jarquin
Summary: This paper proposes a condition-based maintenance system based on artificial intelligence for an online monitoring system of the support bed expansion in a pilot-scale inverse fluidized bed reactor. It uses a single-level sensor as a virtual sensor to achieve a condition-based maintenance strategy for a biofilm inverse fluidizing bed. An artificial neural network is implemented on a Raspberry Pi 4 to estimate signals and maintain the correct operation of the reactor. The system estimates the COD concentration and biogas production flow using the neural network and conductivity sensors.
Review
Chemistry, Analytical
Guillermo Prieto-Avalos, Laura Nely Sanchez-Morales, Giner Alor-Hernandez, Jose Luis Sanchez-Cervantes
Summary: Neurodegenerative diseases are one of the top 10 causes of death worldwide, causing irreversible motor impairments that affect patients, families, and social environments. Using wearable devices to early identify and remotely monitor these motor impairments is one strategy to mitigate the pain of NDDs.
Article
Engineering, Biomedical
Marco J. Del Moral-Argumedo, Carlos A. Ochoa-Zezzati, Ruben Posada-Gomez, Alberto A. Aguilar-Lasserre
Summary: This paper presents a method for multi-class cell segmentation, achieving good performance by utilizing state-of-the-art classification architectures. The approach accurately assesses cervical cell lesions and improves healthcare for patients.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Editorial Material
Biotechnology & Applied Microbiology
Ferran Sanz, Francois Pognan, Thomas Steger-Hartmann, Carlos Diaz, eTRANSAFE Consortium
Summary: Thirteen pharmaceutical companies have collaborated to share and integrate preclinical and clinical data, creating computational resources to improve translational drug safety assessment.
NATURE REVIEWS DRUG DISCOVERY
(2023)
Article
Pharmacology & Pharmacy
Aniek F. Markus, Victoria Y. Strauss, Edward Burn, Xintong Li, Antonella Delmestri, Christian Reich, Can Yin, Miguel A. Mayer, Juan-Manuel Ramirez-Anguita, Edelmira Marti, Katia M. C. Verhamme, Peter R. Rijnbeek, Daniel Prieto-Alhambra, Annika M. Joedicke
Summary: This study aimed to characterize the treatment of Thrombosis with thrombocytopenia syndrome (TTS) and other thromboembolic events after COVID-19 vaccination and compare them with pre-vaccination data. The results showed significant variability in the proportion of people treated across different databases before and after vaccination.
FRONTIERS IN PHARMACOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Pedro Omar Silva-Vasquez, Viviana Yarel Rosales-Morales, Edgard Benitez-Guerrero, Giner Alor-Hernandez, Carmen Mezura-Godoy, Luis Gerardo Montane-Jimenez
Summary: Serious games, which are video games designed for educational purposes, can help teachers enhance students' knowledge. The development of serious games requires knowledge, time, and effort, and specialized tools are needed to assist the process. This study introduces a model for developing serious games in the platformer genre and presents a proof of concept tool based on this model. The tool was used to generate a serious game, which was evaluated in terms of gameplay, mechanics, story, and usability. The evaluation results indicate that the serious game meets the minimum requirements of student audiences, who expect an entertaining and educational game. The results are satisfactory in three out of four areas, with room for improvement in the game's story. This research aims to improve the development time of new serious games and make them more accessible to software engineers and teachers for classroom implementation.
APPLIED SCIENCES-BASEL
(2023)
Article
Health Care Sciences & Services
Jorge Pool-Cen, Hugo Carlos-Martinez, Gandhi Hernandez-Chan, Oscar Sanchez-Siordia
Summary: Mental health problems, including depression, are a global issue. Early diagnosis is crucial, and AI tools can be used for efficient diagnosis. However, there is a lack of data for AI tools in the Spanish language. This study proposes a cross-lingual approach to address this issue and validates the behavior of depression in Mexico during the COVID-19 pandemic.
Article
Medicine, General & Internal
Erica A. Voss, Azza Shoaibi, Lana Yin Hui Lai, Clair Blacketer, Thamir Alshammari, Rupa Makadia, Kevin Haynes, Anthony G. Sena, Gowtham Rao, Sebastiaan van Sandijk, Clement Fraboulet, Laurent Boyer, Tanguy Le Carrour, Scott Horban, Daniel R. Morales, Jordi Martinez Roldan, Juan Manuel Ramirez-Anguita, Miguel A. Mayer, Marcel de Wilde, Luis H. John, Talita Duarte-Salles, Elena Roel, Andrea Pistillo, Raivo Kolde, Filip Maljkovic, Spiros Denaxas, Vaclav Papez, Michael G. Kahn, Karthik Natarajan, Christian Reich, Alex Secora, Evan P. Minty, Nigam H. Shah, Jose D. Posada, Maria Teresa Garcia Morales, Diego Bosca, Honorio Cadenas Juanino, Antonio Diaz Holgado, Miguel Pedrera Jimenez, Pablo Serrano Balazote, Noelia Garcia Barrio, Selcuk Sen, Ali Yagiz ueresin, Baris Erdogan, Luc Belmans, Geert Byttebier, Manu L. N. G. Malbrain, Daniel J. Dedman, Zara Cuccu, Rohit Vashisht, Atul J. Butte, Ayan Patel, Lisa Dahm, Cora Han, Fan Bu, Faaizah Arshad, Anna Ostropolets, Fredrik Nyberg, George Hripcsak, Marc A. Suchard, Dani Prieto-Alhambra, Peter R. Rijnbeek, Martijn J. Schuemie, Patrick B. Ryan
Summary: This study aimed to compare the incidence rates of specific adverse events of interest (AESIs) after COVID-19 infection with historical rates in the general population. The findings showed a significant increase in AESIs after COVID-19, with thromboembolic events being particularly common.
Review
Rheumatology
Alfredo Madrid-Garcia, Beatriz Merino-Barbancho, Alejandro Rodriguez-Gonzalez, Benjamin Fernandez-Gutierrez, Luis Rodriguez-Rodriguez, Ernestina Menasalvas-Ruiz
Summary: Researchers in rheumatology are interested in using artificial intelligence techniques to answer their research questions, resulting in a significant increase in published research on rheumatic and musculoskeletal diseases. This review analyzes research articles published between 2017 and 2021, highlighting the various ways in which data science techniques are being applied in the field of rheumatology.
SEMINARS IN ARTHRITIS AND RHEUMATISM
(2023)
Article
Mathematics
Luis Rolando Guarneros-Nolasco, Giner Alor-Hernandez, Guillermo Prieto-Avalos, Jose Luis Sanchez-Cervantes
Summary: Liver diseases are a significant global health concern, with NAFLD affecting one-third of the population. Researchers are using machine learning algorithms to identify at-risk individuals, and this study examined the effectiveness of nine different algorithms in predicting liver disease development.
Proceedings Paper
Computer Science, Artificial Intelligence
Andrea Alvarez Perez, Ana Iglesias-Molina, Lucia Prieto Santamaria, Maria Poveda-Villalon, Carlos Badenes-Olmedo, Alejandro Rodriguez-Gonzalez
Summary: This paper introduces EBOCA, an ontology that provides a schema for describing concepts and associations in the biomedical domain, along with supporting evidence. The ontology has been evaluated and successfully applied in real scenarios.
KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT, EKAW 2022
(2022)
