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Disciplines
(Field of Science):
- automation, electronics, electrical engineering and space technologies (Engineering and Technology)
- information and communication technology (Engineering and Technology)
- safety engineering (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- medical biology (Medical and Health Sciences )
- pharmacology and pharmacy (Medical and Health Sciences )
- medical sciences (Medical and Health Sciences )
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(Field of Science)
Ministry points: Help
Year | Points | List |
---|---|---|
Year 2024 | 140 | Ministry scored journals list 2024 |
Year | Points | List |
---|---|---|
2024 | 140 | Ministry scored journals list 2024 |
2023 | 140 | Ministry Scored Journals List |
2022 | 140 | Ministry Scored Journals List 2019-2022 |
2021 | 140 | Ministry Scored Journals List 2019-2022 |
2020 | 140 | Ministry Scored Journals List 2019-2022 |
2019 | 140 | Ministry Scored Journals List 2019-2022 |
2018 | 30 | A |
2017 | 30 | A |
2016 | 30 | A |
2015 | 30 | A |
2014 | 30 | A |
2013 | 30 | A |
2012 | 25 | A |
2011 | 25 | A |
2010 | 20 | A |
Model:
Points CiteScore:
Year | Points |
---|---|
Year 2023 | 13.1 |
Year | Points |
---|---|
2023 | 13.1 |
2022 | 10.8 |
2021 | 10.3 |
2020 | 9.8 |
2019 | 9.5 |
2018 | 8 |
2017 | 6.4 |
2016 | 4.9 |
2015 | 4.2 |
2014 | 3.8 |
2013 | 3.8 |
2012 | 4.3 |
2011 | 4.2 |
Impact Factor:
Sherpa Romeo:
Papers published in journal
Filters
total: 2
Catalog Journals
Year 2014
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Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment
PublicationClinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublicationIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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