
The Cedars-Sinai Accelerator offers a mentorship-driven Program to support early-stage companies in developing solutions to improve healthcare and healthcare delivery. Companies accepted into the Program spend three months working closely with mentors from Cedars-Sinai and beyond to accelerate the development, growth, and traction of their products and companies.
2:30pm - 4:00pm with reception to follow.
Join us for the Cedars-Sinai Accelerator Class 9 Demo Day showcasing 10 leading health-tech startups.
52North: 52North offers a medical device that can be used by patients outside of the hospital to monitor their risk of neutropenic sepsis, a life-threatening complication of chemotherapy.
Acorai: Acorai provides a device for heart failure management through noninvasive intracardiac pressure monitoring to help reduce hospitalizations and readmissions.
Alva Health: Alva Health offers a wearable monitoring device designed for early stroke detection.
CARI Health: CARI Health develops a remote medication monitor to enable personalized dosing and real-time medication adherence monitoring.
equalityMD: equalityMD is a community-centric platform for LGBTQ+ patients to share and connect with others.
Machine Medicine: Machine Medicine provides a platform that helps researchers capture and assess motor functioning in patients with neuromodulation devices.
Paperplane Therapeutics: Paperplane Therapeutics designs therapeutic virtual reality video games aimed at improving pain and anxiety management in children undergoing various medical treatments or procedures.
Predicta Med: Predicta Med develops a solution for early detection and treatment selection for undiagnosed autoimmune diseases.
RCE.ai: RCE.ai offers a noninvasive device that monitors cardiac proteins in the blood, empowering emergency medicine physicians and cardiologists in the early assessment of patients presenting with chest pain.
TestDynamics: TestDynamics develops a platform that offers hospitals and physicians one-stop, intelligent access to a wide range of AI models for medical imaging.