(Taken from this UPF news)
Rocket is a unified (cloud-based) platform aimed at assisting clinicians, allowing them to store, visualize and process different types of clinical data: measurements, images, and reports. Being web-based, it allows end-users to access patient information using their smart-phones, tablets or computers, with the only need of internet connection. The platform integrates a computation engine to analyze data in real time, through different methodologies such as decision trees from clinical guidelines, data mining or machine learning, geared toward the improvement of clinical decision making.
One of the key pillars of this platform is the viewer. The Rocket viewer allows visualizing different kinds of data such as medical and biological images, 3D surfaces, electric signals (ECGs) and documents, either from the web or loading information from the local file system. Its code is available open source at the GitHub repository of BCN MedTech where further description, tutorials, and demo videos can be found. The original developers of Rocket are Carlos Yagüe Méndez and María del Pilar García Gracia, both from the Department of Information and Communication Technologies (DTIC).
Rocket platform to explore population clinical data to identify high risk pregnancies
The Rocket platform is already being used in a project granted by the Bill & Melinda Gates Foundation, in collaboration with The Aga Khan University (Karachi, Pakistan). Pakistan is one of the countries where stillbirth rate and early neonatal mortality rates are among the highest in the world. Routine screening of neonatal and placental blood flow through Doppler echocardiography is needed to recommend interventions during pregnancy that can drastically reduce perinatal deaths. However, in developing countries, and especially in rural or challenged regions, the lack of fetal medicine specialists hinders the implantation of these routine screening techniques.
This work has been financed during the last years by the European projects VP2HF (http://vp2hf.eu/), CardioFunXion https://www.upf.edu/web/cardiofunxion), NEUBIAS (http://eubias.org / NEUBIAS /) and the strategic research program Maria de Maetzu of the DTIC (https://www.upf.edu/web/mdm-dtic) that promotes research on the extraction of knowledge guided by data.
The first objective of this project is to use the Rocket platform to allow fetal medicine specialists to store, share and visualize clinical data, at anytime, anywhere, so they can remotely take actions to reduce the burden of perinatal outcomes. Building on this, another objective is to implement data visualization tools within the Rocket platform to explore population clinical data to identify high risk pregnancies, and to explore machine learning algorithms trained with echocardiographic studies to predict those cases at increased risk of adverse perinatal outcomes such as stillbirth, perinatal mortality and other neonatal morbidities. Olga Galí i Pérez, a student of the Bachelor’s degree in Biomedical Engineering of UPF, has recently travelled to Karachi to work towards the integration of the Rocket Platform with the data repositories there.
Developing a clinical interface for a patients with inherited disorders causing sudden cardiac death
“In the next months, we plan to use the Rocket platform in a collaboration with Dra Begoña Benito from Hospital del Mar, which aims at developing a clinical interface for managing and processing familiar data from patients with inherited disorders causing sudden cardiac death. This interface may help clinicians to further understand and prevent such inherited disorders from a family point of view”, said developer’s team.
The Rocket platform will soon be available at the GitHub repository of BCN MedTech.