Serviceeinschränkungen vom 12.-22.02.2026 - weitere Infos auf der UB-Homepage
American Psychological Association 6th edition

Atias D, Ashri S, Goldbourt U, Benyamini Y, Gilad-Bachrach R, Hasin T, Gerber Y, & Obolski U. (2025). Machine learning in epidemiology: An introduction, comparison with traditional methods, and a case study of predicting extreme longevity. Annals of Epidemiology, 110, 23-23. https://doi.org/10.1016/j.annepidem.2025.07.024

ISO-690 (author-date, English)

ATIAS D, ASHRI S, GOLDBOURT U, BENYAMINI Y, GILAD-BACHRACH R, HASIN T, GERBER Y und OBOLSKI U, 2025. Machine learning in epidemiology: An introduction, comparison with traditional methods, and a case study of predicting extreme longevity. Annals of epidemiology. 1 Oktober 2025. Vol. 110, , p. 23-23. DOI 10.1016/j.annepidem.2025.07.024.

Modern Language Association 9th edition

Atias D, Ashri S, Goldbourt U, Benyamini Y, Gilad-Bachrach R, Hasin T, Gerber Y, und Obolski U. „Machine Learning in Epidemiology: An Introduction, Comparison With Traditional Methods, and a Case Study of Predicting Extreme Longevity.“. Annals of Epidemiology, Bd. 110, Oktober 2025, S. 23-23, https://doi.org/10.1016/j.annepidem.2025.07.024.

Mohr Siebeck - Recht (Deutsch - Österreich)

Atias D/Ashri S/Goldbourt U/Benyamini Y/Gilad-Bachrach R/Hasin T u. a.: Machine learning in epidemiology: An introduction, comparison with traditional methods, and a case study of predicting extreme longevity., Annals of epidemiology 2025, 23-23.

Emerald - Harvard

Atias D, Ashri S, Goldbourt U, Benyamini Y, Gilad-Bachrach R, Hasin T, Gerber Y und Obolski U. (2025), „Machine learning in epidemiology: An introduction, comparison with traditional methods, and a case study of predicting extreme longevity.“, Annals of Epidemiology, Vol. 110, S. 23-23.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.