Smart Data Platform

A cloud-based system that integrates healthcare data to enhance decision-making using Artificial Intelligence and Natural Language Processing.

The need of Smart Data Platform

Clinical, scientific practice and administrative processes generates a significant amount of data, both structured and unstructured, but due to the current difficulties in analyzing data in an integrated manner, it is not possible to leverage all the possible benefits from them. Besides that, healthcare companies, also driven by recent initiatives at the Italian and European levels, are increasingly required to implement a model of care based on platforms and data enhancement.

Smart Data Platform framework

The Smart Data Platform is a cloud-based centralized platform of clinical and administrative data. The smart data platform solution has been implemented across various clients belonging to both public and private healthcare sectors.
By centralizing different type of data coming from several areas into a single repository, Laife Reply makes the various company departments able to exploit the enormous capabilities provided by modern models of Artificial Intelligence and pursuing the goal of using data to support decision-making processes in the clinical, research and administrative fields. The platform offers different Big Data frameworks to store and manage structured and unstructured data but also NLP and AI services to extract knowledge from the information ingested into the system.

MAIN FEATURES / DATA


  • Amount of data

    More than 550.0 GB of data inside the platform

  • Number of patients

    More than 1.1 M of patients managed

  • Different sources

    Data coming from scientific research, clinical trial, administrative area and clinical practise

  • Natural language

    NLP, NLU to structure your data

  • Emerging technologies

    AI & Analytics to touch the innovation

Enhancing Data Insights

The architecture of the smart data platform aligns with contemporary data lakehouse frameworks. Initially, raw data are amassed in a centralized file system known as the landing area. From there, the data undergo further processing and integration into a data lake, where they are systematically organized to facilitate efficient access for consumption layers, such as dashboards and applications. On top of this, various Natural Language Processing (NLP) models analyze the unstructured data—specifically medical reports—to autonomously extract pertinent information and deliver insights directly to end users. As the platform's data volume expands, an increasing array of AI models will become available to enhance user capabilities and insights.