Cargando…

Learning the Mental Health Impact of COVID-19 in the United States With Explainable Artificial Intelligence: Observational Study

BACKGROUND: The COVID-19 pandemic has affected the health, economic, and social fabric of many nations worldwide. Identification of individual-level susceptibility factors may help people in identifying and managing their emotional, psychological, and social well-being. OBJECTIVE: This study is focu...

Descripción completa

Detalles Bibliográficos
Autores principales:	Jha, Indra Prakash, Awasthi, Raghav, Kumar, Ajit, Kumar, Vibhor, Sethi, Tavpritesh
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2021
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059787/ https://www.ncbi.nlm.nih.gov/pubmed/33877051 http://dx.doi.org/10.2196/25097

Ejemplares similares

Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study
por: Pal, Ridam, et al.
Publicado: (2022)

Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19
por: Arora, Gunjan, et al.
Publicado: (2021)

A mental models approach for defining explainable artificial intelligence
por: Merry, Michael, et al.
Publicado: (2021)

Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)
por: Meas, Molika, et al.
Publicado: (2022)

Explainable artificial intelligence for mental health through transparency and interpretability for understandability
por: Joyce, Dan W., et al.
Publicado: (2023)

To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems
por: Amann, Julia, et al.
Publicado: (2022)

Causability and explainability of artificial intelligence in medicine
por: Holzinger, Andreas, et al.
Publicado: (2019)

Early prediction of hypothermia in pediatric intensive care units using machine learning
por: Singh, Pradeep, et al.
Publicado: (2022)

VacSIM: Learning effective strategies for COVID-19 vaccine distribution using reinforcement learning
por: Awasthi, Raghav, et al.
Publicado: (2022)

Explainable artificial intelligence as a reliable annotator of archaeal promoter regions
por: Sganzerla Martinez, Gustavo, et al.
Publicado: (2023)

Explainable Artificial Intelligence for Neuroscience: Behavioral Neurostimulation
por: Fellous, Jean-Marc, et al.
Publicado: (2019)

Explainable Artificial Intelligence in Endocrinological Medical Research
por: Webb-Robertson, Bobbie-Jo M
Publicado: (2021)

Artificial intelligence explainability: the technical and ethical dimensions
por: McDermid, John A., et al.
Publicado: (2021)

Explainable Artificial Intelligence for Predictive Modeling in Healthcare
por: Yang, Christopher C.
Publicado: (2022)

Applications of Explainable Artificial Intelligence in Diagnosis and Surgery
por: Zhang, Yiming, et al.
Publicado: (2022)

Explainable artificial intelligence model to predict brain states from fNIRS signals
por: Shibu, Caleb Jones, et al.
Publicado: (2023)

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
por: Amann, Julia, et al.
Publicado: (2020)

Editorial: Explainable Artificial Intelligence (XAI) in Systems Neuroscience
por: Lombardi, Angela, et al.
Publicado: (2021)

Explainable vs. interpretable artificial intelligence frameworks in oncology
por: Bertsimas, Dimitris, et al.
Publicado: (2023)

Beauty is in the explainable artificial intelligence (XAI) of the “agnostic” beholder
por: Laios, Alexandros, et al.
Publicado: (2023)

Explainable Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease
por: Lee, Kwang-Sig, et al.
Publicado: (2022)

Editorial: Explainable artificial intelligence for critical healthcare applications
por: He, Zhe, et al.
Publicado: (2023)

Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes
por: Chandra, Omkar, et al.
Publicado: (2023)

Taming the chaos?! Using eXplainable Artificial Intelligence (XAI) to tackle the complexity in mental health research
por: Roessner, Veit, et al.
Publicado: (2021)

Explainable Artificial Intelligence (XAI) for Deep Learning Based Medical Imaging Classification
por: Ghnemat, Rawan, et al.
Publicado: (2023)

Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences
por: Feng, Jinchao, et al.
Publicado: (2020)

Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability
por: Coeckelbergh, Mark
Publicado: (2019)

Explainable artificial intelligence for heart rate variability in ECG signal
por: K., Sanjana, et al.
Publicado: (2020)

Editorial: Explainable Artificial Intelligence and Neuroscience: Cross-Disciplinary Perspectives
por: Krichmar, Jeffrey L., et al.
Publicado: (2021)

Editorial: Explainable artificial intelligence models and methods in finance and healthcare
por: Caffo, Brian S., et al.
Publicado: (2022)

Patient-level proteomic network prediction by explainable artificial intelligence
por: Keyl, Philipp, et al.
Publicado: (2022)

Explainable artificial intelligence for precision medicine in acute myeloid leukemia
por: Gimeno, Marian, et al.
Publicado: (2022)

Recent Advances in Explainable Artificial Intelligence for Magnetic Resonance Imaging
por: Qian, Jinzhao, et al.
Publicado: (2023)

An explainable artificial intelligence framework for risk prediction of COPD in smokers
por: Wang, Xuchun, et al.
Publicado: (2023)

Machine Learning and Explainable Artificial Intelligence Using Counterfactual Explanations for Evaluating Posture Parameters
por: Dindorf, Carlo, et al.
Publicado: (2023)

A machine learning and explainable artificial intelligence triage-prediction system for COVID-19
por: Khanna, Varada Vivek, et al.
Publicado: (2023)

Mining Trends of COVID-19 Vaccine Beliefs on Twitter With Lexical Embeddings: Longitudinal Observational Study
por: Chopra, Harshita, et al.
Publicado: (2023)

Editorial: Artificial intelligence for mental disorder prevention and diagnosis: Technologies and challenges
por: Zhang, Peiying, et al.
Publicado: (2023)

Joint Banknote Recognition and Counterfeit Detection Using Explainable Artificial Intelligence
por: Han, Miseon, et al.
Publicado: (2019)

Global gene network exploration based on explainable artificial intelligence approach
por: Park, Heewon, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_rh1n275sd21ua44ei5hc9vlh27