Advances in AI-Driven Retention Prediction for Different Chromatographic Techniques: Unraveling the Complexity-Reference-Cited by-同舟云学术

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Advances in AI-Driven Retention Prediction for Different Chromatographic Techniques: Unraveling the Complexity

Published:2023-09-06 Issue: Volume: Page:1-11
ISSN:1040-8347
Container-title:Critical Reviews in Analytical Chemistry
language:en
Short-container-title:Critical Reviews in Analytical Chemistry

Author:

Singh Yash Raj¹,Shah Darshil B.¹,Maheshwari Dilip G.¹,Shah Jignesh S.²,Shah Shreeraj³

Affiliation:

1. Department of Pharmaceutical Quality Assurance, L. J. Institute of Pharmacy, L J University, Ahmedabad, Gujarat, India

2. Department of Pharmaceutical Regulatory Affairs, L. J. Institute of Pharmacy, L J University, Ahmedabad, Gujarat, India

3. Department of Pharmaceutical Technology, L. J. Institute of Pharmacy, L J University, Ahmedabad, Gujarat, India

Publisher

Informa UK Limited

Subject

Analytical Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10408347.2023.2254379

Reference113 articles.

1. Trends in artificial intelligence, machine learning, and chemometrics applied to chemical data

2. Design of Experiments and machine learning for product innovation: A systematic literature review

3. Best practices in machine learning for chemistry

4. Artificial intelligence to deep learning: machine intelligence approach for drug discovery

5. Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional Networks

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