AI: Catalyst for Drug Discovery and Development
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1148-2_18
Reference41 articles.
1. Ahn S, Lee SE, Kim M (2022) Random-forest model for drug–target interaction prediction via Kullback–Leibler divergence. J Cheminform. https://doi.org/10.1186/s13321-022-00644-1
2. Araujo MP, Al-Yaseen W, Innes NP (2020) A road map for designing and reporting clinical trials in paediatric dentistry. Int J Paed Dent 31:14–22
3. Askin S, Burkhalter D, Calado G, El Dakrouni S (2023) Artificial intelligence applied to clinical trials: opportunities and challenges. Health Technol 13:203–213
4. Blanco-González A, Cabezón A, Seco-González A, Conde-Torres D, Antelo-Riveiro P, Piñeiro Á, Garcia-Fandino R (2023) The role of AI in drug discovery: challenges, opportunities, and strategies. Pharmaceuticals 16:891
5. Bodaghi A, Fattahi N, Ramazani A (2023) Biomarkers: promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases. Heliyon 9:e13323
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