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April 24, 2026Open Access

Beyond Gut Feel: Predicting Outcomes of Digital Health Companies

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Authors

EPEstelle PfitzerCKChristoph KauschTKTobias Kowatsch

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Overview

Machine learning predicts success in digital health companies, suggesting enhanced investment strategies.

Key Points

  • The goal is to develop a machine learning model that predicts the success of digital health companies.
  • Utilized data on 10,245 companies founded since 2000.
  • Trained several models, including logistic regression, random forest, and XGBoost.
  • Improved model accuracy using features derived from unstructured text with a large language model.
  • The ensemble model achieved the best discrimination with an AUC of 0.934 ± 0.017.
  • Model accuracy (63%) surpassed mean investor accuracy (52%).
  • Adding LLM-derived features improved performance statistically significantly (P < 0.05).

Cite This Study

Pfitzer et al. (2026) studied this question.

synapsesocial.com/papers/69eb099a553a5433e34b3fd3https://doi.org/10.3929/ethz-c-000798862
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