MACHINE LEARNING FOR HEALTH INFORMATICS

Worldwide initiatives in aggregating Healthcare data, and the healthcare sector moving towards value-based care raise the need for Biomedical Analysts trained to handle Healthcare specific use cases. Typically confined within the domain of Public Health only, today the scope of data-driven informatics in healthcare has extended to clinical outcome prediction, unstructured text data analysis, image classification, and even prevention of disease. As with any data science problem, solving a use case of healthcare requires domain-specific knowledge in addition to general data science skills. A mature Health Informatics company will need to have the perfect balance between healthcare experts and data scientists. Considering the scope and degree of complexity in health informatics, this course has been designed to skill up individuals who may come from the healthcare domain or data science domain.

A Guided Omics Logic Training Program with an experienced industry mentor. Hands-on training based on case studies, with a focus on the positive impact of analytics on the patient-physician relationship.

Click here to Pre-Register for the Machine Learning in Health Informatics

OL- What is Health Informatics
OL-Health Informatics -IT Sector

Wealth of Data: Data Sources in Health Informatics 

Data sources are always heterogeneous in Health Informatics and above all, it's mostly semi-structured and unstructured. Even if data is structured, data cleaning will take up massive efforts. So far public health data, Electronic Health Records, Investigation results, Images (USG, CT- Scan, Pathology), and medical devices present in the hospital were considered to be rich data sources. However, with the advent of wearables and home-based care, continuous time-series data and remote patient-monitoring devices are going to occupy a huge volume of healthcare data in the future. Also is present a huge amount of genomic and other omics data, an important pillar of precision medicine that also needs to be integrated with the use cases of Health Informatics.

Solution Categories in Health Informatics

Healthcare problems are use-case and population specific. Solutions can be preventive, curative, or insight generative. The easiest type of healthcare solution which can be easily communicated is a supervised prediction model where a specific clinical outcome needs to be predicted by integrating multiple data sources; for example, predicting the risk of hospitalization for an individual with uncontrolled hypertension. Hence there will be multiple levels of challenges: Data acquisition, Data structuring, Workflow selection, and Cross-validation. A brief workflow of such a model is given below. Besides this, other models will also be covered along with real-world use cases.

Case-Based Learning | Mentor-Guidance | Beginner-Advance Levels

The digitization of healthcare systems in clinical settings, and an explosion of personal data collection devices provide the opportunity of using data for revolutionizing approaches to provide care at all levels.  with an emphasis on precision medicine and person-centered care. The ability to take advantage of this Big Data opportunity requires expertise at the intersection of health informatics, data science, and computational modeling.

 

Health Informatics: About the Course

Who is the course for?

  • This course is designed for anyone interested in Health informatics data, Machine learning, and artificial intelligence applications in healthcare for local problems and help address global health problems.
  • This beginner-level course is available for students (Undergraduates & Postgraduates), researchers (Ph.D. & Post-Doctoral, Faculty), and healthcare professionals (Industry).

How Practical is this course?

  • This course is designed with introductory sessions to help beginners and practical and hands-on sessions with mentors to learn and practice what is being taught (Intermediate level with recorded sessions and personalized learning support by the team). 
  • This course follows the omics logic pedagogy of asynchronous coursework mentor-guided sessions, practical assignments, and quizzes.
Ol- Health Informatics Tenure

Enroll today for 45/60/90 Days 

45 Days

  • Batch Live Sessions - 10 (Duration: 45 days) 
  • Scheduled between (11 Jan - 11 Feb)
  • Weekly Live sessions: Two meetings/week 
  • Session Length: 90 Mins (Including Q&A) 
  • Delivery: 100% Online (Zoom meetings and OmicsLogic Portal)
  • OmicsLogic Coursework and T-BioInfo Server Access

 

 

                                                                                                                  

 

 

 60 Days

  • Batch Live Sessions - 10 (Duration: 45 days) 
  • Scheduled between (11 Jan - 11 Feb)
  • Weekly Live sessions: Two meetings/ week 
  • Group Live Sessions- 4 (Duration: 15 days)
  • Scheduled between 12 Feb- 29 Feb
  • Session Length: 90 Mins (Including Q&A) 
  • Delivery: 100% Online (Zoom meetings and OmicsLogic Portal)
  • 04 Live Session (Interaction with groups - cohorts on coursework, practical assignments, and project proposals)
  • OmicsLogic Coursework and T-BioInfo Server Access


90 Days

  • Batch Live Sessions - 10 (Duration: 45 days) 
  • Scheduled between 11 Jan - 11 Feb
  • Weekly Live sessions: Two meetings/ week 
  • Group Live Sessions- 4 (Duration: 15 days)
  • Group/ One-on-One Session (3 Sessions/Participant: 30 days) (March)
  • Session Length: 90 Mins (Including Q&A) 
  • Delivery: 100% Online (Zoom meetings and OmicsLogic Portal)
  • 03 Live Session/participants / Group and one-on-one (Interaction with groups - cohorts on coursework, practical assignments, and project publication)
  • OmicsLogic Coursework and T-BioInfo Server Access

Below are the payment checkout links for the tenures mentioned above:

Note: For Low-Income Countries scholarship opportunities are available, please reach out to us and our team at: marketing@omicslogic.com and we will find the best possible way for you to participate and get the best outcomes from the training program.

We also have the option for financial assistance with weekly/monthly installment options.

WhatsApp.svg+91-9876134120

Whom will you learn with?

Mentors & Experts

Dr. Jit Sarkar

PhD Life Sciences Senior Bioinformatics Data Scientist, Elucidata

Dr. RL Narayanan

OmicsLogic Research Consultant & Mentor Pine Biotech

Mr. Elia Brodsky

Co-Founder & CEO, Pine Biotech

Program Session 

DETAILS

Session Title

Topics & Resources 

Session 1: Overview
  • AI in transforming Healthcare
  • Investments in AI for Healthcare
  • How is Data Science transforming Healthcare?
  • Challenges in Health Informatics
  • Predictive Model Workflow
  • Multimodal Approach for Precision Medicine
  • Q & A

Session 2: Data Sources

  • Review of Session 1 and Recap
  • Data Sources
  • Health Records
  • Imaging Data
  • Histopathological Data
  • Multi-omics Data
  • Miscellaneous Data
  • Q & A 

Session 3: Heart Disease and Risk Factors

  • Review of Session 2 and Recap
  • Heart Disease and Risk Factors
  • Defining the Target variable
  • Identifying the Important Predictor variables
  • Building the Model
  • Model Interpretation
  • Model Evaluation
  • Q & A

Session 4: Data & Analysis

  • Review of Session 3 and Recap
  • Hands-on Demo of the Case Study
  • Practical Session with the Mentor
  • Q & A


Session 5: Conclusion

  • Review of Session 4 and Recap
  • Clinical Implications of Predictive Modelling
  • Other possible Use Cases
  • Real-world application
  • Q & A

 

Session 6: Clustering and Exploratory Data Analysis

  • Recap
  • Clustering Heart Disease Patients
  • Exploratory Data Analysis (EDA)
  • Clustering techniques
  • Post-clustering tasks
  • Q & A

Associated Resources: (Documents, links)

Asynchronous:


Sesson 7: Example Project

  • Review of Session 6 and Recap
  • Hands-on Demo of the Case Study
  • Practical Session with the mentor
  • Q & A

Session 8: Example Project

  • Review of Session 7 and Recap
  • Clinical Implications of Clustering
  • Other possible Use Cases
  • Real-world application
  • Q & A

Session 9: What Next?

  • Review of Session 8 and Recap
  • Other Cutting-edge areas of Health Informatics
  • Project Assignments
  • Q & A

Session 10: Summary

  • Recap: Overview
  • Recap: Data Sources
  • Recap: Case Study-1
  • Recap: Case Study-2
  • Health Informatics Research Proposal and Collaborative Projects
  •  Next Steps
  • Q & A

Career Guidance & Certification

You will get career guidance from Industry leaders, Subject Matter Experts, and 24/7 Support from the OmicsLogic team to develop important and relevant skillsets and experience-building opportunities. This industry experience provides real-world knowledge that supports students in their networking and job searches.

 

Register for the Webinar & Program details:

HI-OL.003
USF-Health Informatics
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Payment Checkout Links for 45/60/90 Days Tenure

Note: For Low-Income Countries scholarship opportunities are available, please reach out to us and our team at: marketing@omicslogic.com and we will find the best possible way for you to participate and get the best outcomes from the training program.

We also have the option for financial assistance with weekly/monthly installment options.

WhatsApp.svg+91-9876134120

Beginner Level Subscription (45 Days access)

  • Batch Live Sessions - 10 (Duration: 45 days) 
  • Scheduled between 11 Jan - 11 Feb
  • Weekly Live sessions: Two meetings/week 
  • Session Length: 90 Mins (Including Q&A) 
  • Delivery: 100% Online (Zoom meetings and OmicsLogic Portal)

Intermediate Level Subscription (60 Days access)

  • Batch Live Sessions - 10 (Duration: 45 days) 
  • Scheduled between 11 Jan - 11 Feb
  • Weekly Live sessions: Two meetings/ week 
  • Group Live Sessions- 4 (Duration: 15 days)
  • Scheduled between 12 Feb- 29 Feb
  • Session Length: 90 Mins (Including Q&A) 
  • Delivery: 100% Online (Zoom meetings and OmicsLogic Portal)
  • 04 Live Session (Interaction with groups - cohorts on coursework, practical assignments, and project proposals)

Advanced Level Subscription (90 Days access)

  • Batch Live Sessions - 10 (Duration: 45 days) 
  • Scheduled between 11 Jan - 11 Feb
  • Weekly Live sessions: Two meetings/ week 
  • Group Live Sessions- 4 (Duration: 15 days)
  • Group/ One-on-One Session (3 Sessions/Participant: 30 days) (March)
  • Session Length: 90 Mins (Including Q&A) 
  • Delivery: 100% Online (Zoom meetings and OmicsLogic Portal)
  • 03 Live Session/participants / Group and one-on-one (Interaction with groups - cohorts on coursework, practical assignments, and project proposals)