Table of Contents

Mentor Based

AI and Digital Technologies: Pioneering Healthcare Transformation

Transforming Healthcare with Cutting-Edge AI and Digital Technologies

Explore

Enroll now for early access of e-LMS

MODE
Online/ e-LMS

TYPE
Mentor Based

LEVEL
Moderate

DURATION
8 Weeks

About

This course is designed to provide healthcare professionals with a deep understanding of how digital technologies are transforming healthcare systems, processes, and patient care.

Aim

This program covers strategic planning, implementation of digital health solutions, data analytics, and the integration of emerging technologies such as AI, IoT, and blockchain in healthcare settings.

Program Objectives

To understand the scope and impact of digital transformation in the healthcare industry.
To learn about the strategic planning and execution of digital health projects.
To gain insights into the use of data analytics and AI in improving healthcare outcomes.
To explore the role of IoT, wearable technologies, and remote patient monitoring in enhancing patient care.
To understand the ethical, privacy, and security considerations in digital healthcare.
To study the implementation of blockchain technology in healthcare data management for enhanced security and interoperability.

Program Structure

Module 1: Introduction to AI in Healthcare

Overview of AI in Medicine: Evolution of AI in healthcare, core concepts of AI and machine learning.
Key Digital Technologies in Healthcare: IoT, telemedicine, and wearable tech.
AI’s Role in Healthcare Transformation: Understanding how AI drives change in patient care, hospital operations, and research.

Module 2: Data and Digital Health Infrastructure

Healthcare Data Ecosystems: Types of healthcare data, data sources, and interoperability.
Data Privacy and Security: HIPAA, GDPR, and key considerations for patient data protection.
Data Cleaning and Preprocessing: Preparing healthcare data for AI applications.

Module 3: Machine Learning Applications in Diagnostics

Supervised Learning for Diagnostic Tools: Applications in radiology, pathology, and genomics.
Unsupervised Learning for Disease Detection: Clustering techniques for early disease detection and anomaly detection.
Natural Language Processing (NLP) in Healthcare: Using NLP for analyzing medical records, literature, and patient feedback.

Module 4: Predictive Analytics and Patient Outcome Forecasting

Predictive Analytics in Healthcare: Identifying trends in patient data, predicting patient outcomes.
Time-Series Analysis for Monitoring Health: Using time-series data from wearables and medical devices.
Risk Stratification Models: AI models for patient risk scoring and hospital readmission predictions.

Module 5: Personalized Medicine and AI-Driven Treatment Planning

Precision Medicine and Genomics: AI’s role in personalized treatment, drug discovery, and genomics.
Clinical Decision Support Systems (CDSS): AI-based tools for aiding clinical decisions.
Real-World Applications: Case studies of personalized treatment plans and adaptive care.

Module 6: Robotics and Automation in Healthcare

Surgical Robots and Automation: Overview of robotic surgery and automation in healthcare operations.
AI in Robotic Process Automation (RPA): Automating administrative tasks and improving efficiency.
Wearable and Assistive Technologies: Wearable AI devices for continuous health monitoring.

Module 7: Remote Care and Telemedicine Innovations

Telehealth and AI: Role of AI in enhancing remote consultations, diagnostics, and treatment.
Mobile Health (mHealth) Technologies: App-based monitoring, remote patient management.
IoT in Healthcare: Role of connected devices in patient care and remote monitoring.

Module 8: AI Ethics, Regulation, and Patient Trust

Ethical Considerations in AI: Fairness, accountability, and transparency in AI models.
Regulations and Compliance: Key regulations governing AI in healthcare (FDA, EMA).
Building Trust with AI in Healthcare: Importance of transparency and patient-centered AI applications.

Module 9: Emerging Trends and Future of AI in Healthcare

Blockchain for Secure Data Sharing: Using blockchain for interoperability and secure patient records.
Augmented Reality (AR) and Virtual Reality (VR) in Healthcare: Applications in training, diagnostics, and treatment.
Quantum Computing in Drug Discovery and Healthcare: Potential applications of quantum computing in AI healthcare.

Module 10: Capstone Project and Industry Case Studies

Industry Case Studies: Reviewing successful AI implementations in healthcare (e.g., IBM Watson, Google Health).
Capstone Project: Development and presentation of a healthcare AI solution, applying course learnings.

Participant’s Eligibility

Healthcare Professionals: Doctors, nurses, and healthcare administrators looking to integrate AI and digital technologies into their practices.
IT Professionals: Developers, data scientists, and IT managers interested in applying their skills to the healthcare sector.
Students and Researchers: Individuals in healthcare, computer science, and related fields aiming to specialize in healthcare technology.
Business Leaders: Executives and managers in healthcare organizations seeking to understand the impact and implementation of digital transformation.

Program Outcomes

Participants will have a comprehensive understanding of digital transformation in healthcare, including its challenges and opportunities.
Graduates will be equipped to lead digital health projects, from strategic planning to execution.
Learners will be skilled in applying data analytics and AI to solve healthcare problems and improve patient outcomes.
Participants will understand the application and impact of IoT and wearable technologies in patient monitoring and care.
Graduates will be knowledgeable about the use of blockchain for secure and efficient healthcare data management.
Learners will be prepared to navigate ethical, privacy, and security considerations in the implementation of digital health solutions.

Mentors

AI Mentor

Mr. Dushyant Tiwari

Scripta Lex Law Firm.

Biography

AI Mentor

Adv. Karan Choudhary

Unity Law Attorneys

Biography

AI Mentor

Akanksha Kamthe

Digismvada Consultancy Pvt.Ltd

Biography

More Mentors

Fee Structure

Fee: INR 21,499 USD 291

We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!

List of Currencies