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Filename: drivers/Session_files_driver.php
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File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
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Filename: Session/Session.php
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Backtrace:
File: /var/www/html/index.php
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Function: require_once
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Filename: helpers/my_audit_helper.php
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Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1057
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3175
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
Efficient chemical synthesis is critical for the production of organic chemicals, particularly in the pharmaceutical industry. Leveraging machine learning to predict chemical synthesis and improve the development efficiency has become a significant research focus in modern chemistry. Among various machine learning models, the Transformer, a leading model in natural language processing, has revolutionized numerous fields due to its powerful feature-extraction and representation-learning capabilities. Recent applications demonstrated that Transformer models can also significantly enhance the performance in chemical synthesis tasks, particularly in reaction prediction and retrosynthetic planning. This article provides a comprehensive review of the applications and innovations of Transformer models in the qualitative prediction tasks of chemical synthesis, with a focus on technical approaches, performance advantages, and the challenges associated with applying the Transformer architecture to chemical reactions. Furthermore, we discuss the future directions for improving the applications of Transformer models in chemical synthesis.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11821105 | PMC |
http://dx.doi.org/10.3390/molecules30030493 | DOI Listing |
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