Syncmind Lab

Secure collaborative learning platform for brain 🧠 research  #DecentralizedMedicine

Adaptation of domain in medical data is crucial for several reasons. Firstly, data stands as a pivotal factor for success in drug discovery and clinical trials across all stages. However, the exponential growth of medical data, doubling every 18 months, presents challenges. Despite this surge, individual clinic-level data remains insufficient, compounded by the fact that over 30% of data contains artifacts, diminishing diagnostic accuracy. These artifacts stem from various sources, including different formats such as DICOM, JPEG, and PNG, as well as variations in device models, each with unique characteristics. For instance, differences in settings, calibrations, and processing algorithms contribute to data noise. Additionally, the need for amalgamating multimodal data, like CT, MRI, fMRI and textual information, arises for comprehensive analysis. Addressing these challenges requires approaches for secure storage and efficient integration of data from diverse sources and formats. Ensuring the safety of data storage while facilitating seamless data fusion from various origins and types becomes imperative for advancing medical research and clinical practice

Unveiling the Brain's Complexity: Exploring fMRI Analysis with MindNet https://lnkd.in/eGRXscQ8

We are delighted to announce that Syncmind Lab is joining the Microsoft for Startups Pegasus program. This collaboration will enable us to leverage the resources of the Microsoft ecosystem to propel our research and platform towards new breakthroughs in clinical trials and drug discovery

Here's a simple introduction about the approach we use to interact with patient data