Here’s How Big Data Analytics is Changing the Face of Precision Medicine

Here’s How Big Data Analytics is Changing the Face of Precision Medicine

Publication date: Sep 21, 2019

“Big health data” generated from patient health records, diagnosis, genomic sequencing, medical research, smart devices, wearables holds the potential to transform healthcare & deliver personalized medicine Opinions expressed by Entrepreneur contributors are their own.

Related: 4 Ways Savvy Entrepreneurs Stay Focused on Health When Traveling for Business -Big health data” is the immense data generated from patient health records, diagnosis, treatments, genomic sequencing, medical research, smart devices, wearable, and various other sources.

This data holds the potential to transform the healthcare industry, from precision medicine and drug research to population screening and effective decision making.

Longitudinal patient health records now enable tracking of real-time clinical data of individual patients.

Successful integration of these multiple data sets is key to precision medicine.

Latest technologies are also being used to structured clinical data, identify patterns in the patient population, cluster/segregate population using clinical and molecular data points, identify mutations in large sets of genetic data, automate workflows, and help clinicians make informed decisions in real-time.

All stakeholders in precision medicine ecosystem can utilize this data: healthcare providers can improve patient care, patients can educate themselves and collaborate with their physicians, researchers can improve study designs, health technology community can design and improve the data platforms, decision-makers can use this to maximize the health benefits and improve healthcare coverage and access.

Challenges with Utilization of EHRs and Genomic Data in India Patient health records in the form of EHRs are currently heterogeneous – stored in multiple sources, formats, and databases.

Insufficient amount of genomic data is collected in India due to limited research and development; India has around 18% of the world’s population, but only represents less than 1% of existing global genetic data.

Medicine is all set to undergo a digital transformation – the future will see how healthcare community progresses from anatomy-based medicine to an all-inclusive, data-driven medicine that integrates data science, data analytics, digital health, and precision medicine.

Concepts Keywords
AI Biotechnology
Asia Computational methods algorithms
Big Data Healthcare technologies
Caucasian Artificial intelligence
China Health informatics
Chronic Diseases Personalized medicine
DBT Big data
Deep Learning Systems biology
Digital Health Precision medicine
Digital Transformation Evidence-based medicine
Disposable Income Articles
Economic Growth Branches of biology
Ecosystem Medicine
EHR Computational methods algorithms
Genetic Healthcare access
Genetics Healthcare burden
Genome Healthcare technologies
Genomic Sequencing Data healthcare providers
Healthcare Platforms decision makers
Healthcare Industry Radiology imaging
India Real time
Interoperability Healthcare
Japan Classification systems
MarketWatch
Medicine
Oncology
Precision Medicine
Prognosis
Public Domain
Radiology
Semantics
Subgroup
Synergy
USD
Velocity
Wearables

Semantics

Type Source Name
disease MESH chronic diseases
gene UNIPROT DBT
gene UNIPROT SET
disease MESH diagnosis
disease MESH lifestyle
disease MESH genetic markers
drug DRUGBANK C31G
gene UNIPROT LAT2
drug DRUGBANK Tropicamide
gene UNIPROT LARGE1
disease MESH community
disease MESH development
gene UNIPROT ELOVL6
gene UNIPROT FANCE
disease DOID Face

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