Cloud Healthcare API

Course Feature
  • Cost
    Free
  • Provider
    ThaiMOOC
  • Certificate
    Free Certification
  • Language
    English
  • Start Date
    On-Demand
  • Learners
    No Information
  • Duration
    7.00
  • Instructor
    /
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1.5
27 Ratings
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Course Overview

❗The content presented here is sourced directly from ThaiMOOC platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 19th, 2023]

This course provides an overview of the Cloud Healthcare API and how it can be used to bridge the gap between care systems and applications built on Google Cloud. Participants will learn how to use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets. By the end of the course, participants will have a better understanding of how to use the Cloud Healthcare API to connect their data to advanced Google Cloud capabilities.

[Applications]
The application of this course can be seen in the healthcare industry, where the Cloud Healthcare API can be used to bridge the gap between care systems and applications built on Google Cloud. This course provides the knowledge and skills necessary to use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets. This can help healthcare organizations to better manage their data and improve patient care.

[Career Paths]
1. Cloud Healthcare API Developer: Cloud Healthcare API Developers are responsible for developing and maintaining applications that use the Cloud Healthcare API to bridge the gap between care systems and applications built on Google Cloud. They must be knowledgeable in the industry standard FHIR, HL7v2 and DICOM formats, and be able to use the Cloud Healthcare API to ingest and process data. They must also be able to use Cloud Dataflow, BigQuery, and Cloud Machine Learning Engine to stream data processing, analytics, and machine learning. As the healthcare industry continues to move towards cloud-based solutions, the demand for Cloud Healthcare API Developers is expected to grow.

2. Cloud Healthcare Data Scientist: Cloud Healthcare Data Scientists are responsible for analyzing and interpreting healthcare data using the Cloud Healthcare API. They must be knowledgeable in the industry standard FHIR, HL7v2 and DICOM formats, and be able to use the Cloud Healthcare API to ingest and process data. They must also be able to use Cloud Dataflow, BigQuery, and Cloud Machine Learning Engine to stream data processing, analytics, and machine learning. As the healthcare industry continues to move towards cloud-based solutions, the demand for Cloud Healthcare Data Scientists is expected to grow.

3. Cloud Healthcare Solutions Architect: Cloud Healthcare Solutions Architects are responsible for designing and implementing cloud-based healthcare solutions using the Cloud Healthcare API. They must be knowledgeable in the industry standard FHIR, HL7v2 and DICOM formats, and be able to use the Cloud Healthcare API to ingest and process data. They must also be able to use Cloud Dataflow, BigQuery, and Cloud Machine Learning Engine to stream data processing, analytics, and machine learning. As the healthcare industry continues to move towards cloud-based solutions, the demand for Cloud Healthcare Solutions Architects is expected to grow.

4. Cloud Healthcare Security Engineer: Cloud Healthcare Security Engineers are responsible for ensuring the security of cloud-based healthcare solutions using the Cloud Healthcare API. They must be knowledgeable in the industry standard FHIR, HL7v2 and DICOM formats, and be able to use the Cloud Healthcare API to ingest and process data. They must also be able to use Cloud Dataflow, BigQuery, and Cloud Machine Learning Engine to stream data processing, analytics, and machine learning. As the healthcare industry continues to move towards cloud-based solutions, the demand for Cloud Healthcare Security Engineers is expected to grow.

[Education Paths]
1. Bachelor's Degree in Computer Science: A Bachelor's Degree in Computer Science is a great way to gain the skills and knowledge necessary to work with Cloud Healthcare API. This degree program will provide students with a comprehensive understanding of computer science fundamentals, including programming, data structures, algorithms, and software engineering. Additionally, students will learn about cloud computing, machine learning, and artificial intelligence, which are all essential for working with Cloud Healthcare API. As the healthcare industry continues to embrace digital transformation, the demand for computer science professionals with expertise in cloud computing and healthcare technology is expected to grow.

2. Master's Degree in Health Informatics: A Master's Degree in Health Informatics is a great way to gain the skills and knowledge necessary to work with Cloud Healthcare API. This degree program will provide students with a comprehensive understanding of healthcare information systems, including data management, analytics, and security. Additionally, students will learn about cloud computing, machine learning, and artificial intelligence, which are all essential for working with Cloud Healthcare API. As the healthcare industry continues to embrace digital transformation, the demand for health informatics professionals with expertise in cloud computing and healthcare technology is expected to grow.

3. Doctor of Nursing Practice (DNP): A Doctor of Nursing Practice (DNP) is a great way to gain the skills and knowledge necessary to work with Cloud Healthcare API. This degree program will provide students with a comprehensive understanding of nursing practice, including patient care, health promotion, and disease prevention. Additionally, students will learn about cloud computing, machine learning, and artificial intelligence, which are all essential for working with Cloud Healthcare API. As the healthcare industry continues to embrace digital transformation, the demand for nursing professionals with expertise in cloud computing and healthcare technology is expected to grow.

4. Master's Degree in Health Data Science: A Master's Degree in Health Data Science is a great way to gain the skills and knowledge necessary to work with Cloud Healthcare API. This degree program will provide students with a comprehensive understanding of data science, including data analysis, data visualization, and machine learning. Additionally, students will learn about cloud computing, machine learning, and artificial intelligence, which are all essential for working with Cloud Healthcare API. As the healthcare industry continues to embrace digital transformation, the demand for data science professionals with expertise in cloud computing and healthcare technology is expected to grow.

Course Syllabus

Ingesting FHIR Data with the Healthcare API

In this lab you will learn the basic functionalities of Cloud Healthcare API using the Fast Healthcare Interoperability (FHIR) data model.

Machine Learning Predictions with FHIR and Healthcare API

In this lab you will create a prediction pipeline for FHIR resources using Cloud Healthcare API and AI Platform.

Ingesting HL7v2 Data with the Healthcare API

In this lab you will discover and use the basic functionality of Cloud Healthcare API using HL7v2 messages.

Ingesting DICOM Data with the Healthcare API

In this lab you will learn the basic functionality of Cloud Healthcare API using Digital Imaging and Commmuniations in Medicine (DICOM) data model.

De-identifying DICOM Data with the Healthcare API

Use the de-identification functionality of Cloud Healthcare API with the Digital Imaging and Communications in Medicine (DICOM) data model.

Streaming HL7 to FHIR Data with Healthcare API

In this lab, you will explore some of the features of Cloud Healthcare API (HCAPI) to stream HL7v2 messages into HCAPI datastores and convert HL7v2 to FHIR and import the FHIR data into BigQuery for analytical use.
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