AI In Medicine
Medical Sub-Specialities

AI In Medicine For Critical Care professionals

AI In Medicine For Laboratory Medicine professionals

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CCAIM - For Critical Care Professionals

Thorough understanding of Potential for AI innovations in the healthcare
Use of AI in clinical medicine, patient monitoring, clinical queries, precision diagnosis (like Pathology, Radiology, Genomics etc) and care,
Use of some basic AI tools like LLM, NLP, Generative AI etc. in healthcare service quality improvement
Use of AI in regular practice by medical professionals
How medical research, report writing, peer review can be enhanced using AI tools
Use of AI in legacy applications, social media contents for efficient output
Exploring how it can be applied to enhance healthcare data management for enhanced diagnosis and patient monitoring,
Understand and evaluations of various AI applications
Practical adoption and Deployment challenges
Practical demonstration with capstone for leading digital transformation

Program Anatomy

Total Duration : 42 Hours (4 Hrs per week) / Two & half Months

Model of Delivery : Online

Eligibility : Physicians, Clinicians, Medical Students , (Postgraduate), Graduate Nurse for those connected to ICU, Emergency and other critical care ,

Certification : Dual Certification -

1. Healthcare Sector Skill Council, (HSSC) MSDE, GOI.

2. Universal AI University

Lesson Structure

43 hours | 15 Modules | 3 Section Assessment | 1 Research Project | 1 Capstone Project

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CCAIM - For Laboratory Medicine Professionals

Thorough understanding of Potential for AI innovations in the healthcare
Use of AI in clinical medicine, patient monitoring, clinical queries, precision diagnosis (like Pathology, Radiology, Genomics etc) and care,
Use of some basic AI tools like LLM, NLP, Generative AI etc. in healthcare service quality improvement
Use of AI in regular practice by medical professionals
How medical research, report writing, peer review can be enhanced using AI tools
Use of AI in legacy applications, social media contents for efficient output
Exploring how it can be applied to enhance healthcare data management for enhanced diagnosis and patient monitoring,
Understand and evaluations of various AI applications
Practical adoption and Deployment challenges
Practical demonstration with capstone for leading digital transformation