Medsensio are collaborating with a variety of organisations
Optimising on ri-sonic
At Medsensio, we are proud to collaborate with Riester, a leading manufacturer of medical diagnostic equipment, to refine and enhance our lung and heart sound algorithms for seamless integration with their innovative digital stethoscope, the ri-sonic. This partnership combines Medsensio's expertise in advanced signal processing and machine learning with Riester's commitment to delivering high-quality medical devices, resulting in a state-of-the-art diagnostic tool that elevates the practice of auscultation.
Together, we are working tirelessly to fine-tune our algorithms to detect and analyze even the most subtle nuances in lung and heart sounds, enabling healthcare professionals to make more accurate and timely diagnoses. Ultimately, this synergy between Medsensio and Riester will revolutionize the field of auscultation, contributing to improved patient outcomes and more efficient healthcare delivery.
University of Linköping
Medsensio is thrilled to collaborate with the prestigious University of Linköping on the groundbreaking project CHALS (Computerized Heart And Lung Sounds). Our partnership aims to advance the understanding of lung and heart sounds by recording and analyzing them for research purposes. Leveraging Medsensio's cutting-edge signal processing and machine learning technology, we work closely with the university's dedicated researchers to collect, process, and interpret high-quality auscultation data. This joint effort will deepen our knowledge of cardiovascular and pulmonary health, fostering new discoveries and innovations in the diagnosis and treatment of related diseases. By working with the University of Linköping on CHALS, Medsensio reaffirms its commitment to driving the future of medical research and improving patient outcomes worldwide.
University of Lodz
Medsensio has partnered up with researchers from the Medical University of Lodz, including Dr. Krystian Bartczak and Professor Joanna Miłkowska-Dymanowska from the Department of Pulmonology, in a collaboration that not only enhances our medical AI capabilities but also positions the university at the forefront of technological advancements in medical artificial intelligence.
This cutting-edge collaboration allows us to refine and optimize our algorithms, leading to more precise diagnostics and improved patient outcomes. Furthermore, the joint efforts of Medsensio and the researchers enable the exploration of new possibilities in AI-driven diagnostics and treatment strategies.
Medsensio are open to collaborating with most types of organisations. We specialise in both commercial and academic R&D, with medical AI as our core focus area.
Our partners are typically interested in one or more of the following areas:
Remote patient monitoring
AI in medicine
Workflow optimisation in healthcare
Clinical research data analysis
As part of our commitment to delivering ethical AI, Medsensio is teaming up with the ENACT consortium in developing and testing a process for evaluating the ethical consideration of digital solutions.
ENACT (Ethical risks assessmeNt of Artificial intelligenCe in pracTice) is lead by Leonora Onarheim Bergsjø. The project group consists of Sintef Digital, Østfold University College Faculty of Teacher Education and Languages, Norwegian Open AI Lab at NTNU, Institute for Informatics at UiO, Center for e-health at UiA, University College London and Imperial College London.
Additional participating research networks are Norwegian Artificial Intelligence Research Consortium (NORA) and Innovationnetwork Cluster for Applied AI/Smart Innovation Norway, together with Norwegian Council for Digital Ethics (NORDE).