Callisia was founded during the pandemic by a multidisciplinary team of engineers, researchers, and medical professionals who participated in a regional initiative to combat COVID-19. To become the world's first software platform capable of harnessing the power of telemedicine to predict clinical risks, placing both patients and medical staff at the center of our approach. In doing so, we aim to revolutionize the healthcare industry by providing personalized, high-quality, and accessible care to all.
We combine medical and computer skills to offer safe and timely access to medical care through telemedicine. Our web-based, multiplatform software called CLS is connected to IoT hardware devices and optical biosensors to provide personalized, high-quality, and accessible medical care to everyone.
Specifically, CLS platform will classify patients based on their real-time care needs, providing doctors with support for patient management. Furthermore, the creation of a patient-centered medical system aims to anticipate clinical risk by using artificial intelligence algorithms to enhance the effectiveness of healthcare. The system utilizes artificial intelligence algorithms to create a predictive model based on a distributed network, which anonymously analyzes data to identify useful patterns for data correlation. The system employs both unsupervised and supervised learning, guided by the conjectures and assessments of the Callisia scientific team, to optimize the accuracy of predictions and recommendations.
The CLS platform offers secure remote connection of vital patient data, enabling doctors to access the data even when patients are discharged from the healthcare facility. This improves care continuity while ensuring patient privacy through the use of advanced encryption and data security techniques. In addition to continuous analysis of vital parameters, Callisia retains the flow of received data, creating a patient monitoring history. Callisia can leverage the collected data to analyze patient health and prevent potential illnesses. In fact, among Callisia's future developments are the use of artificial intelligence algorithms to define predictive models specific to patient subpopulations (such as surgical or medical patients, low or high-intensity care patients, oncology patients, etc.), the development of early warning systems, and the implementation of standardized pathways aimed at reducing medical errors.
Currently, we are launching our SpinOff with the University of Politecnica delle Marche as a 4% shareholder, and three other companies holding 32% of the shares. Our SpinOff has recently won a regional competition with a prize of €20k, and we have also secured €100k in funding from one of the companies involved.
