StethoMe

stethome.com

StethoMe, an AI startup focussed on the world of healthcare and telemedicine. StethoMe is the first system that detects abnormalities in the respiratory system. StethoMe relies on medical AI algorithms (CE 2274) working together with a wireless stethoscope and dedicated application. The electronic StethoMe stethoscope is a precision medical device intended for performing auscultation of the respiratory system and heart. The stethoscope connects to the smartphone via Bluetooth and enables making high quality recordings of auscultation sounds in a dedicated application. After the examination is finished, the sounds recorded are sent to the physician’s audiovisual panel where a unique sound StethoMe AI analysis preview is provided. StethoMe AI is the certified medical system intended for sound analysis supporting the diagnostic process. The system relies on artificial intelligence algorithms. It maximizes the treatment efficiency and increases the reliability of diagnosis. StethoMe AI detects pathological sounds in the respiratory system of children with high accuracy and provides information automatically about respiratory and heart rates. StethoMe ensures also control over examination quality thanks to it can be used by both patients at their homes and by medical centers that provide telemedicine services. The device and AI algorithms have been certified in EU as a class 2a medical device (CE2274). The StethoMe project can be implemented thanks to the trust of investors - SpeedUp Group, Programa.pl, TDJ Pitango Ventures and Manta Ray VC. Main achievements: - Baillie Gifford Discovery Competition - Winner, 2019 - EC2VC Pitch Competition - Winner, 2019 - IOT/WT Innovation World Cup, Healthcare - Winner, 2018 - Startup World Cup & Summit - European Winner, BioTech Award, 2018 - CESawards - Best Social Impact Startup, Best Newcomer, 2017 - Future X Healthcare start-up Award - 3rd Place Winner, Audience Award, 2017 - Hardware Massive CEE - Winner, 2017 - Philips Innovation Challenge - Champion Award, 2016