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Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection methodology was evaluated with the leave-one-out validation method combined with a Monte Carlo-based bootstrap step. The clinical motivation for this project is that ischemic stroke patients may receive acute thrombolytic treatment at hospitals, dramatically reducing or abolishing symptoms. A microwave system is suitable for prehospital use, and therefore has the potential to allow significantly earlier diagnosis and treatment than today.