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2024 연구성과별 연구자 정보 (157 / 2344)

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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
An Integrated Review of Health Care in Child and Adolescent Cancer Survivors Based on Roy's Adaptation Model Lee, Eunjoo Lee, E 2 교신저자 Kyungpook Natl Univ, Coll Nursing, 680 Gukchaebosang Ro, Daegu 41944, South Korea jewelee@knu.ac.kr;
An Integrated Review of Health Care in Child and Adolescent Cancer Survivors Based on Roy's Adaptation Model Lee, Eunjoo Lee, E 2 교신저자 Kyungpook Natl Univ, Res Inst Nursing Innovat, Coll Nursing, Daegu, South Korea jewelee@knu.ac.kr;
An Intelligent Hybrid Machine Learning Model for Sustainable Forecasting of Home Energy Demand and Electricity Price Parizad, Banafshe Parizad, B 1 RMIT Univ, Sch Engn, Melbourne 3000, Australia 0009-0004-6373-1553 Parizad, Banafshe s4023374@student.rmit.edu.au;hranjbar@deakin.edu.au;alijamali@knu.ac.kr;hamid.khayyam@rmit.edu.au;
An Intelligent Hybrid Machine Learning Model for Sustainable Forecasting of Home Energy Demand and Electricity Price Ranjbarzadeh, Hassan Ranjbarzadeh, H 2 Deakin Univ, Sch Engn, Geelong 3217, Australia s4023374@student.rmit.edu.au;hranjbar@deakin.edu.au;alijamali@knu.ac.kr;hamid.khayyam@rmit.edu.au;
An Intelligent Hybrid Machine Learning Model for Sustainable Forecasting of Home Energy Demand and Electricity Price Jamali, Ali Jamali, A 3 RMIT Univ, Sch Engn, Melbourne 3000, Australia AAX-5841-2020 Jamali, Ali 0000-0003-2592-6187 Jamali, Ali s4023374@student.rmit.edu.au;hranjbar@deakin.edu.au;alijamali@knu.ac.kr;hamid.khayyam@rmit.edu.au;
An Intelligent Hybrid Machine Learning Model for Sustainable Forecasting of Home Energy Demand and Electricity Price Jamali, Ali Jamali, A 3 Kyungpook Natl Univ, Sch Elect Engn, Dept Artificial Intelligence, Daegu 37224, South Korea AAX-5841-2020 Jamali, Ali 0000-0003-2592-6187 Jamali, Ali s4023374@student.rmit.edu.au;hranjbar@deakin.edu.au;alijamali@knu.ac.kr;hamid.khayyam@rmit.edu.au;
An Intelligent Hybrid Machine Learning Model for Sustainable Forecasting of Home Energy Demand and Electricity Price Khayyam, Hamid Khayyam, H 4 교신저자 RMIT Univ, Sch Engn, Melbourne 3000, Australia 0000-0001-9784-1452 Khayyam, Hamid s4023374@student.rmit.edu.au;hranjbar@deakin.edu.au;alijamali@knu.ac.kr;hamid.khayyam@rmit.edu.au;
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Maghsoudi, Omid Haji Maghsoudi, OH 1
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Chung, Liam Il Young Chung, LIY 2 IQU-0821-2023 Chung, Liam Il-Young
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Lee, Seyoung Lee, S 3
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Lee, Jeeyeon Lee, J 4
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Kim, Haseok Kim, H 5 MDT-5309-2025 Kim, Haseok
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Hiremath, Amogh Hiremath, A 6 AAO-3178-2021 Hiremath, Amogh
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Zhang, Kai Zhang, K 7
An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer Cantor, Diego Cantor, D 8
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