Exploring the Predictability of Bacterial Vaginosis in Reproductive Age Women using Longitudinal Vaginal Microbe Abundance and pH Data

Oudshoorn, S.

LIACS Thesis Repository

These webpages contain theses and reports by students affiliated with the various bachelor and master programmes offered at the Leiden Institute of Advanced Computer Science (LIACS), the computer science and artificial intelligence department of Leiden University.
Note: this thesis repository might be incomplete for certain programmes.

Master Computer Science

The following thesis was written by a student in the 2021-2022 class of the Master Computer Science programme at Leiden University.

Thesis details

Title	Exploring the Predictability of Bacterial Vaginosis in Reproductive Age Women using Longitudinal Vaginal Microbe Abundance and pH Data
Student	Oudshoorn, S.
Programme	Master Computer Science
Year	2021-2022
Supervisors	Cao, dr. L. (Lu) Dr. CJ Jenkins (second supervisor)
Thesis	Open Thesis PDF

Citation details

Oudshoorn, S., Exploring the Predictability of Bacterial Vaginosis in Reproductive Age Women using Longitudinal Vaginal Microbe Abundance and pH Data, Thesis Master Computer Science, LIACS, Leiden University, 2022.