Language Models for Predicting Organic Synthesis Procedures
In optimizing organic chemical synthesis, researchers often face challenges in efficiently generating viable synthesis procedures that conserve time and resources in laboratory settings. This paper systematically analyzes multiple approaches to efficiently generate synthesis procedures for a wide va...
Saved in:
| Main Authors: | Mantas Vaškevičius, Jurgita Kapočiūtė-Dzikienė |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/24/11526 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches
by: Muhammad Shoaib Farooq, et al.
Published: (2025-07-01) -
How much can we save by applying artificial intelligence in evidence synthesis? Results from a pragmatic review to quantify workload efficiencies and cost savings
by: Seye Abogunrin, et al.
Published: (2025-01-01) -
Evolving Journal Policies for Ethical Use of Generative AI in Scientific Publishing
by: Afifa Ehsan, et al.
Published: (2025-06-01) -
Evaluating the Performance of Artificial Intelligence-Based Large Language Models in Orthodontics—A Systematic Review and Meta-Analysis
by: Farraj Albalawi, et al.
Published: (2025-01-01) -
Application of artificial intelligence in intelligent healthcare
by: WANG Zuheng, et al.
Published: (2025-02-01)