Examples

Retrospectively validated AI model allows early detection of Alzheimer's 6 years in advance
 

• https://doi.org/10.1007/s13167-020-00216-z
• https://www.nature.com/articles/s41598-018-29433-3

Innovative AI approach allows identification of prognostically relevant molecular cancer subtypes based on multi-omics data

•  https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3465-2

AI approach allows more efficient identification of new drug target structures
 

• https://pubmed.ncbi.nlm.nih.gov/32750869/

Innovative AI approach allows the generation of realistic synthetic patient trajectories
 

• https://www.frontiersin.org/articles/10.3389/fdata.2020.00016/full

AI allows for stratification of Alzheimer and Parkinson patients via molecular disease mechanisms - a step towards Precision medicine in neurology

• https://www.nature.com/articles/s41598-020-76200-4
  

New AI approach allows for clustering of multivariate longitudinal patient trajectories and detection of progression subtypes in Alzheimer's and Parkinson's Disease

• https://academic.oup.com/gigascience/article/8/11/giz134/5626377

An explainable AI approach allows for predicting comorbidity risks of individual epileptic patients using large scale clinical routine data. Within the Fraunhofer Center for Machine Learning we developed a demonstrator to showcase this approach.

• Patient Demonstrator: Explainable AI Models for Predicting Personalized Risk Profiles
• https://doi.org/10.3389/frai.2021.610197

Towards realizing the vision of precision medicine: AI allows for predicting response to anti-epileptic drug

• https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awab108/6178276