Cargando…

Human-Centered Explainable Artificial Intelligence: Automotive Occupational Health Protection Profiles in Prevention Musculoskeletal Symptoms

In automotive and industrial settings, occupational physicians are responsible for monitoring workers’ health protection profiles. Workers’ Functional Work Ability (FWA) status is used to create Occupational Health Protection Profiles (OHPP). This is a novel longitudinal study in comparison with pre...

Descripción completa

Detalles Bibliográficos
Autores principales:	Mollaei, Nafiseh, Fujao, Carlos, Silva, Luis, Rodrigues, Joao, Cepeda, Catia, Gamboa, Hugo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368597/ https://www.ncbi.nlm.nih.gov/pubmed/35954919 http://dx.doi.org/10.3390/ijerph19159552

Ejemplares similares

A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
por: Assunção, Ana, et al.
Publicado: (2022)

Predictive Factors of Short-Term Related Musculoskeletal Pain in the Automotive Industry
por: Assunção, Ana, et al.
Publicado: (2021)

How to Implement Automotive Fault Diagnosis Using Artificial Intelligence Scheme
por: Gong, Cihun-Siyong Alex, et al.
Publicado: (2022)

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

Artificial intelligence in musculoskeletal ultrasound imaging
por: Shin, YiRang, et al.
Publicado: (2021)

Artificial Intelligence in Musculoskeletal Oncological Radiology
por: Vogrin, Matjaz, et al.
Publicado: (2020)

Relationship of Occupational and Non-Occupational Stress with Smoking in Automotive Industry Workers
por: Hassani, Somayeh, et al.
Publicado: (2014)

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)

Explainable Artificial Intelligence for COVID-19 Diagnosis Through Blood Test Variables
por: Thimoteo, Lucas M., et al.
Publicado: (2022)

The promise and limitations of artificial intelligence in musculoskeletal imaging
por: Debs, Patrick, et al.
Publicado: (2023)

A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering
por: Thunold, Håvard Horgen, 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)

Evaluation of musculoskeletal tumors in the new era of artificial intelligence
por: Costa, Flávia Martins
Publicado: (2018)

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

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)

Occupational stress and musculoskeletal symptoms in a Tunisian footwear industry
por: Rmadi, N., et al.
Publicado: (2022)

Current and emerging artificial intelligence applications for pediatric musculoskeletal radiology
por: Offiah, Amaka C.
Publicado: (2021)

Work-related musculoskeletal disorders in the automotive industry due to repetitive work - implications for rehabilitation
por: Spallek, Michael, et al.
Publicado: (2010)

High-Dynamic-Range Tone Mapping in Intelligent Automotive Systems
por: Shopovska, Ivana, et al.
Publicado: (2023)

Explainable artificial intelligence-based edge fuzzy images for COVID-19 detection and identification
por: Hu, Qinhua, et al.
Publicado: (2022)

Relationship between Lighting and Noise Levels and Productivity of the Occupants in Automotive Assembly Industry
por: Akbari, Jafar, et al.
Publicado: (2013)

Interaction of Physical Exposures and Occupational Factors on Sickness Absence in Automotive Industry Workers
por: Valirad, Fateme, et al.
Publicado: (2015)

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)

A mental models approach for defining explainable artificial intelligence
por: Merry, Michael, 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)

Cannot write session to /tmp/vufind_sessions/sess_kvr282dt3u5lij4eeq7ketf42d