Case Study: Klinikum Stuttgart achieves 95%+ tumor diagnosis accuracy with Palisade NeuralTools

Klinikum Stuttgart - Customer Case Study

Klinikum Stuttgart researchers at Katharinenhospital used Palisade NeuralTools to tackle the challenge of histological classification and grading of brain tumors, a critical step because treatment and outcomes depend heavily on assigned grade. Dr. José R. Iglesias-Rozas applied the tool to predict a malignancy coefficient (1.00–4.00) from ten discrete histological features across a cohort of 786 tumor cases.

Palisade’s NeuralTools neural-network solution was trained on 629 cases and validated on 157 independent cases, delivering 98.58% accuracy on the training set and 95% accuracy on the test set; clinicians also praised the program’s speed and ease of handling numeric and categorical variables. These results position Palisade NeuralTools for wider deployment at Klinikum Stuttgart as the team plans to extend analysis to decades of data covering over 8,000 patients to improve diagnostic consistency and treatment decision support.

Klinikum Stuttgart

José R. Iglesias-Rozas

Associate Professor