Dabdoub, F., Colangelo, M. and Aljumah, M., 2022. Artificial intelligence in healthcare and biotechnology: a review of the Saudi experience. Journal of Artificial Intelligence &Cloud Computing, 107: 2-6. DOI: doi.org/ 10.47363/ JAICC/ 2022(1)107
Fenning, T.M. and Gershenzon, J., 2002. Where will the wood come from? Plantation forests and the role of biotechnology. Trends in Biotechnology, 20: 291-96. DOI: 10.1016/S0167-7799(02)01983-2
Fetzer, J.H. 1990. What is Artificial Intelligence?. In: Artificial Intelligence: Its Scope and Limits. Studies in Cognitive Systems, vol 4. Springer, Dordrecht. DOI: doi.org/10.1007/978-94-009-1900-6_1
Fiorani, F. and Schurr, U., 2013. Future scenarios for plant phenotyping. Annual review of plant biology, 64: 267-91. DOI: doi.org/10.1146/annurev-arplant-050312-120137
Hesami, M. and Jones, A.M.P., 2020. Application of artificial intelligence models and optimization algorithms in plant cell and tissue culture. Applied Microbiology and Biotechnology, 104: 9449-85. DOI: doi.org/10.1007/s00253-020-10888-2
Holmes, J., Sacchi, L. and Bellazzi, R., 2004. Artificial intelligence in medicine. The Annals of The Royal College of Surgeons of England Home, 86: 334-8. DOI: doi.org/10.1308/147870804290
Holzinger, A., Saranti, A. and Mueller, H., 2021a. KANDINSKYPatterns--An experimental exploration environment for Pattern Analysis and Machine Intelligence. arXiv. DOI: doi.org/ 10.48550/arXiv.2103.00519
Holzinger, A., Weippl, E., Tjoa, A.M. and Kieseberg, P., 2021b, August. Digital transformation for sustainable development goals (sdgs)-a security, safety and privacy perspective on ai. In International cross-domain conference for machine learning and knowledge extraction, 1-20. Springer. DOI: doi.org/10.1007/978-3-030-84060-0_1
Holzinger, A., Keiblinger, K., Holub, P., Zatloukal, K. and Müller, H., 2023. AI for life: Trends in artificial intelligence for biotechnology. New Biotechnology, 74, pp.16-24. DOI: doi.org/10.1016/j.nbt.2023.02.001
Johnson, P.C., Laurell, C., Ots, M. and Sandström, C., 2022. Digital innovation and the effects of artificial intelligence on firms’ research and development–Automation or augmentation, exploration or exploitation?. Technological Forecasting and Social Change, 179: 121636. DOI: doi.org/10.1016/j.techfore.2022.121636
Kallem, S.R., 2012. Artificial intelligence algorithms. IOSR Journal of Computer Engineering, 6(3), pp.1-8.
Kumar, R. and Saha, P., 2022. A review on artificial intelligence and machine learning to improve cancer management and drug discovery. International Journal for Research in Applied Sciences and Biotechnology, 9: 149-56. DOI: doi.org/10.31033/ijrasb.9.3.26
Levin, J.M., Oprea, T.I., Davidovich, S., Clozel, T., Overington, J.P., Vanhaelen, Q., Cantor, C.R., Bischof, E. and Zhavoronkov, A., 2020. Artificial intelligence, drug repurposing and peer review, Nature Biotechnology, 38: 1127-31.DOI: doi.org/10.1038/s41587-020-0686-x
Márquez-Chamorro, A.E., Asencio-Cortés, G., Santiesteban-Toca, C.E. and Aguilar-Ruiz, J.S., 2015. Soft computing methods for the prediction of protein tertiary structures: A survey. Applied Soft Computing, 35: 398-410.DOI: doi.org/10.1016/j.asoc.2015.06.024
Massabni, A.C. and da Silva, G.J., 2019. Biotechnology and Industry 4.0: The professionals of the future. International Journal of Advances in Medical Biotechnology-IJAMB, 2: 45-53. doi.org/10.25061/2595-3931/IJAMB/2019.v2i2.39
Melkozernov, A.N. and Sorensen, V., 2021. What drives bio-art in the twenty-first century? Sources of innovations and cultural implications in bio-art/biodesign and biotechnology. AI & SOCIETY, 36: 1313-21. DOI: doi.org/10.1007/s00146-020-00940-0
Nothdurft, A., Gollob, C., Kraßnitzer, R., Erber, G., Ritter, T., Stampfer, K. and Finley, A.O., 2021. Estimating timber volume loss due to storm damage in Carinthia, Austria, using ALS/TLS and spatial regression models. Forest Ecology and Management, 502, p.119714.DOI: doi.org/10.1016/j.foreco.2021.119714
Holzinger, A., Saranti, A., Angerschmid, A., Retzlaff, C.O., Gronauer, A., Pejakovic, V., Medel-Jimenez, F., Krexner, T., Gollob, C. and Stampfer, K., 2022. Digital transformation in smart farm and forest operations needs human-centered AI: challenges and future directions. Sensors, 22(8), p.3043. DOI: doi.org/10.3390/s22083043
Quazi, S. 2022. 'Artificial intelligence and machine learning in precision and genomic medicine', Medical Oncology, 39: 120. DOI: doi.org/10.1007/s12032-022-01711-1
Ribaut, J.M., De Vicente, M.C. and Delannay, X., 2010. Molecular breeding in developing countries: challenges and perspectives. Current opinion in plant biology, 13(2), pp.213-218. DOI: doi.org/10.1016/j.pbi.2009.12.011
Shah, P., Kendall, F., Khozin, S., Goosen, R., Hu, J., Laramie, J., Ringel, M. and Schork, N., 2019. Artificial intelligence and machine learning in clinical development: a translational perspective. NPJ digital medicine, 2(1), p.69. DOI: doi.org/10.1038/s41746-019-0148-3
)