• Jagreet Kaur Gill
  • computer-vision

Solutions for Building Healthcare Analytics Platform

Solutions for Building Healthcare Analytics Platform

Introduction to Healthcare Analytics

There are a variety of techniques available that are expected to examine these varied kinds of data. Analyzing healthcare data will allow physicians to recognize the patterns that are still uncovered in the data. It will also help them to make a patient profile of individuals and can estimate the likelihood of a patient to undergo from a particular medical complexity in the near future accurately.


Challenges for Building Healthcare Analytics Platform

  • Enhance the efficiency of diagnoses.
  • Prescribing Preventive medicine and health.
  • Providing results to doctors in a digital form.
  • Using predictive analysis to uncovers patterns that couldn't be previously revealed.
  • Providing Real-Time monitoring

Technical Challenges

  • To develop data exchange and interoperability architecture to provide a personalized care to the patient.
  • To develop the AI based Analytical platform for integrating multi-sourced data.
  • To propose a Predictive and Prescriptive Modelling Platform for physicians to reduce the semantic gap for accurate diagnosis.

Solution offerings for Building Healthcare Analytics Platfrom

Predictive and Prescriptive Analysis

  • Developed data exchange and interoperability architecture to provide personalized care to the patient using the data extracted from their reports.
  • Developed the AI based Analytical platform for integrating all the medical test reports at one place.
  • Developed a Predictive and Prescriptive Modelling Platform for physicians to reduce the semantic gap for accurate diagnosis.

Text Analysis

  • General Health Reports (GHR) dataset is used to train the model which was accumulated by collecting the reports from Hospitals.
  • These reports are then converted to digital form so that the above types of analytics can be performed.

Image Analysis

  • Digital Database for Screening Mammography Dataset (DDSM) is used to train the Image Analysis model.
  • Generative Adversarial Networks (GAN) is used as the main Deep learning algorithm.

Genomic Data Analysis

  • Most of the diseases now are genetic, but the genetic labels and the conditions have not been established.
  • Genomic Data Analysis enables more in-depth knowledge of the relationships between different genetic tags, modifications, and state has notable potential that supports the evolution of several genetic therapies to heal the diseases.

Real-Time Data Analytics

The concept of IoT is used to collect the data, After collection of data following steps are used -

  • Data Ingestion
  • Data Collector
  • Data Processing
  • Data Storage
  • Data Query
  • Data Visualization

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