Calculator for predicting the probability of faculty promotion in an academic medical centre.

ABSTRACT:

Objective

The academic medical centre (AMC), with over 2200 faculty members, annually manages approximately 300 appointments and promotions. Considering these large numbers, we explored whether machine learning could predict the probability of obtaining promotional approvals.

Methods

We examined variables related to academic promotion using predictive analytical methods. The data included candidates' publications, the H-index, educational contributions and leadership or service within and outside the AMC.

Results

Of the five methods employed, the random forest algorithm was identified as the 'best' model through our leave-one-out cross-validation model evaluation process.

Conclusions

To the best of our knowledge, this is the first study on the AMC. The develope

SUBMITTER: Yeo MM 

PROVIDER: S-EPMC12038130 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature