American Psychological Association 6th edition

Natarajan, S., Ahmed, J., Sundarraj, R., Vinay, V., Shetty, S., Jose, N. P., Chowdappa, S., & Carnelio, S. (2025). Tooth shape and sex estimation: a 3 D geometric morphometric landmark-based comparative analysis of artificial neural networks, support vector machines, and Random Forest models. 3 Biotech, 15(8). https://doi.org/10.1007/s13205-025-04439-7

ISO-690 (author-date, English)

NATARAJAN, Srikant, AHMED, Junaid, SUNDARRAJ, Ruban, VINAY, Varenya, SHETTY, Shravan, JOSE, Nidhin Philip, CHOWDAPPA, Sharada and CARNELIO, Sunitha, 2025. Tooth shape and sex estimation: a 3 D geometric morphometric landmark-based comparative analysis of artificial neural networks, support vector machines, and Random Forest models. 3 Biotech. 1 August 2025. Vol. 15, no. 8, . DOI 10.1007/s13205-025-04439-7.

Modern Language Association 9th edition

Natarajan, S., J. Ahmed, R. Sundarraj, V. Vinay, S. Shetty, N. P. Jose, S. Chowdappa, and S. Carnelio. “Tooth Shape and Sex Estimation: A 3 D Geometric Morphometric Landmark-Based Comparative Analysis of Artificial Neural Networks, Support Vector Machines, and Random Forest Models”. 3 Biotech, vol. 15, no. 8, Aug. 2025, https://doi.org/10.1007/s13205-025-04439-7.

Mohr Siebeck - Recht (Deutsch - Österreich)

Natarajan, Srikant/Ahmed, Junaid/Sundarraj, Ruban/Vinay, Varenya/Shetty, Shravan/Jose, Nidhin Philip et al.: Tooth shape and sex estimation: a 3 D geometric morphometric landmark-based comparative analysis of artificial neural networks, support vector machines, and Random Forest models, 3 Biotech 2025,

Emerald - Harvard

Natarajan, S., Ahmed, J., Sundarraj, R., Vinay, V., Shetty, S., Jose, N.P., Chowdappa, S. and Carnelio, S. (2025), “Tooth shape and sex estimation: a 3 D geometric morphometric landmark-based comparative analysis of artificial neural networks, support vector machines, and Random Forest models”, 3 Biotech, Vol. 15 No. 8, available at:https://doi.org/10.1007/s13205-025-04439-7.

Warning: These citations may not always be 100% accurate.