MIT Sloan School of Management
Artificial Intelligence in Health Care online short course
Explore how machine learning and artificial intelligence can be applied in health care to overcome challenges and improve processes.
Start date
13 November 2024
Course duration
6 weeks
Excluding orientation
Language
English
Access resources from start date
Effort
6–8 hours per week
Self-paced learning online
Course overview
The combined percentage of surveyed health care organizations that are in some way focused on increasing their proportion of AI-assisted applications.
Accenture (Jan, 2019).
The projected value of the AI health care market by 2021.
Business News Daily (Jun, 2019).
Duration: 6 weeks (excluding orientation)
The medical industry constantly strives to improve patient care, and better prediction is crucial in achieving this goal. Machine learning (ML) and artificial intelligence (AI) have proven to be effective tools for enhancing diagnosis, personalizing treatments, and understanding disease progression.
The Artificial Intelligence in Health Care online short course offered by the MIT Sloan School of Management and the MIT J-Clinic is a great option for those interested in exploring the potential impact of AI in healthcare. The course provides a comprehensive overview of AI's applications and limitations in the healthcare industry, examines the challenges it can help address, and highlights successful AI deployments through industry case studies.
Regina Barzilay, world-renowned for her work in AI and breast cancer detection, leads the course, providing valuable insights and knowledge from MIT, a leading institution for developing ML methods with health care applications.
Is this course for you?
Regardless of whether you work in finance or engineering, this program can provide you with an understanding of how artificial intelligence and machine learning can revolutionize the healthcare industry. By taking this course, you'll gain a deeper appreciation for the issues that AI technology and techniques can address in health care. The artificial intelligence in healthcare course covers critical topics such as the fundamentals of ML, neural networks, and deep learning, making it easy to apply what you learn directly to health care roles.
Machine Learning
ML is an AI field that employs algorithms to learn from data and generate predictions. This program introduces you to ML algorithms and their application in the healthcare industry.
Neural Networks
The MIT Sloan Artificial Intelligence in Health Care online course delves into various neural network types and their applications in health care data. Neural networks, a ML algorithm, are particularly effective at tasks like image recognition and classification.
Deep Learning
Moreover, the MIT AI in healthcare course provides a primer on deep learning. Deep learning is the practice of using artificial neural networks with many layers to identify complex data patterns. It is a machine learning subfield focusing on algorithms learning from unstructured or unlabeled data. Through this program, you'll learn about deep learning techniques and how they are employed in health care.
Computer Science Experts
The course is taught by experts in computer science from MIT and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). CSAIL is one of the world's leading AI research centers. The program's faculty members are at the forefront of their field and are developing state-of-the-art technology that is already being used in various industries.
Course overview
Introduction
Duration: 6 weeks (excluding orientation)
The medical industry constantly strives to improve patient care, and better prediction is crucial in achieving this goal. Machine learning (ML) and artificial intelligence (AI) have proven to be effective tools for enhancing diagnosis, personalizing treatments, and understanding disease progression.
The Artificial Intelligence in Health Care online short course offered by the MIT Sloan School of Management and the MIT J-Clinic is a great option for those interested in exploring the potential impact of AI in healthcare. The course provides a comprehensive overview of AI's applications and limitations in the healthcare industry, examines the challenges it can help address, and highlights successful AI deployments through industry case studies.
Regina Barzilay, world-renowned for her work in AI and breast cancer detection, leads the course, providing valuable insights and knowledge from MIT, a leading institution for developing ML methods with health care applications.
Is this course for you?
Regardless of whether you work in finance or engineering, this program can provide you with an understanding of how artificial intelligence and machine learning can revolutionize the healthcare industry. By taking this course, you'll gain a deeper appreciation for the issues that AI technology and techniques can address in health care. The artificial intelligence in healthcare course covers critical topics such as the fundamentals of ML, neural networks, and deep learning, making it easy to apply what you learn directly to health care roles.
Machine Learning
ML is an AI field that employs algorithms to learn from data and generate predictions. This program introduces you to ML algorithms and their application in the healthcare industry.
Neural Networks
The MIT Sloan Artificial Intelligence in Health Care online course delves into various neural network types and their applications in health care data. Neural networks, a ML algorithm, are particularly effective at tasks like image recognition and classification.
Deep Learning
Moreover, the MIT AI in healthcare course provides a primer on deep learning. Deep learning is the practice of using artificial neural networks with many layers to identify complex data patterns. It is a machine learning subfield focusing on algorithms learning from unstructured or unlabeled data. Through this program, you'll learn about deep learning techniques and how they are employed in health care.
Computer Science Experts
The course is taught by experts in computer science from MIT and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). CSAIL is one of the world's leading AI research centers. The program's faculty members are at the forefront of their field and are developing state-of-the-art technology that is already being used in various industries.
What will set you apart
An AI decision framework to help you evaluate the suitability of AI technologies within your work context.
Insights into the AI opportunities available across a range of health care contexts, from hospital management to disease diagnosis.
An overview of AI and ML fundamentals, specifically through the lens of its applicability in health care.
An understanding of AI’s practical implementation and design challenges.
Knowledge of the potential of natural language processing, data analytics, and ML within health care. Course curriculum
Orientation module
Welcome to your Online Campus
Module 1
AI and machine learning — Applications and foundations
Module 2
Using AI for disease diagnosis and patient monitoring
Module 3
Natural language processing and data analytics in health care
Module 4
Interpretability in machine learning — Benefits and challenges
Module 5
Patient risk stratification and augmenting clinical workflows
Module 6
Taking an integrated approach to hospital management and optimization
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Faculty Director
Regina Barzilay
School of Engineering Distinguished Professor for AI and Health, MIT Center for Machine Learning in Health; AI Faculty Lead, Jameel Clinic
Earn a certificate of completion from MIT Sloan
Explore the potential of AI and ML in health care, and earn an official digital certificate of completion from MIT Sloan School of Management.
This program also counts toward an MIT Sloan Executive Certificate, which you can earn by completing four programs; three from your chosen certificate track and one completed in person. Find out more.
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