Výsledky vyhledávání - "Aram Bahrini"

Akademický článek

Understanding the Relationship Between Mood Symptoms and Mobile App Engagement Among Patients With Breast Cancer Using Machine Learning: Case Study

Autor: Anna N Baglione, Lihua Cai, Aram Bahrini, Isabella Posey, Mehdi Boukhechba, Philip I Chow

Publikováno v: JMIR Medical Informatics, Vol 10, Iss 6, p e30712 (2022)

BackgroundHealth interventions delivered via smart devices are increasingly being used to address mental health challenges associated with cancer treatment. Engagement with mobile interventions has been associated with treatment success; however, the

Externí odkaz: https://doaj.org/article/fbc18055e2a240b592f8e01a2844b5a5

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A Systematic Literature Review of MABAC Method and Applications: An Outlook for Sustainability and Circularity

Autor: Ali Ebadi Torkayesh, Erfan Babaee Tirkolaee, Aram Bahrini, Dragan Pamucar, Amir Khakbaz

Publikováno v: Informatica. :1-34

Multiple Criteria Decision-Making (MCDM) is one of the most reliable and applicable decision-making tools to address real-life complex and multi-dimensional problems in accordance with the concepts of sustainable development and circular economy. Alt

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d2ce3f548823d3437c78e0d00d5ec6a
https://doi.org/10.15388/23-infor511

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Improving Patient Flow in a Healthcare Clinic Post COVID-19: A Data Validation and Exploratory Analysis Approach

Autor: Aditi Jain, Aram Bahrini, Eric Nour, Harshal Patel, Emily Riggleman, Tyson Wittmann, Karen Measells, Kimberly Dowdell, Sara L. Riggs, Robert J. Riggs

Publikováno v: 2023 Systems and Information Engineering Design Symposium (SIEDS).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::31de6e634e9fbee9b8bc586d9df0936d
https://doi.org/10.1109/sieds58326.2023.10137848

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A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting

Autor: Reza Paki, Hossein Abbasimehr, Aram Bahrini

Publikováno v: Neural Computing & Applications

The COVID-19 pandemic has disrupted the economy and businesses and impacted all facets of people's lives. It is critical to forecast the number of infected cases to make accurate decisions on the necessary measures to control the outbreak. While deep

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::947dcd32b2eb8d9f3a58884bb1986366
https://doi.org/10.1007/s00521-021-06548-9

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A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models

Autor: Hossein Abbasimehr, Reza Paki, Aram Bahrini

Publikováno v: Sustainable Computing: Informatics and Systems. 38:100863

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b956f6bbdadbb50c3de04734d1d87438
https://doi.org/10.1016/j.suscom.2023.100863

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Optimization of Patient Flow and Process for a Primary Care Clinic During the COVID-19 Pandemic

Autor: Claire Dozier, Alexandra Schmid, Bryce Huffman, Margaret Cusack, Sarah Saas, Wei Wu, Aram Bahrini, Robert J. Riggs, Kimberly Dowdell, Karen Measells

Publikováno v: 2022 Systems and Information Engineering Design Symposium (SIEDS).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9d2ae4885a326a39ddce7a57f8829daa
https://doi.org/10.1109/sieds55548.2022.9799404

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Understanding the Relationship Between Mood Symptoms and Mobile App Engagement Among Patients With Breast Cancer Using Machine Learning: Case Study

Autor: Anna N Baglione, Lihua Cai, Aram Bahrini, Isabella Posey, Mehdi Boukhechba, Philip I Chow

Publikováno v: JMIR medical informatics. 10(6)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d75667f6b4b0ecc19079a1e03351893a
https://pubmed.ncbi.nlm.nih.gov/35653183

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Understanding the Relationship Between Mood Symptoms and Mobile App Engagement Among Patients With Breast Cancer Using Machine Learning: Case Study (Preprint)

Autor: Anna N Baglione, Lihua Cai, Aram Bahrini, Isabella Posey, Mehdi Boukhechba, Philip I Chow

BACKGROUND Health interventions delivered via smart devices are increasingly being used to address mental health challenges associated with cancer treatment. Engagement with mobile interventions has been associated with treatment success; however, th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::811a6a786332ddb586d508a8235913fc
https://doi.org/10.2196/preprints.30712

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Improving the performance of deep learning models using statistical features: The case study of COVID‐19 forecasting

Autor: Hossein Abbasimehr, Reza Paki, Aram Bahrini

Publikováno v: Mathematical Methods in the Applied Sciences

COVID-19 pandemic has affected all aspects of people's lives and disrupted the economy. Forecasting the number of cases infected with this virus can help authorities make accurate decisions on the interventions that must be implemented to control the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f9cb4d1ad22c4ae5f16be9077f54a7c
http://europepmc.org/articles/PMC8242522

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