The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events Specialist
Harness the power of AI to elevate modern-day medical treatments
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March 2, 2023
7 weeks, online
5–7 hours per week
US$2,600 US$2,314 or get US$260 off with a referral
Our participants tell us that taking this program together with their colleagues helps to share common language and accelerate impact.
We hope you find the same. Special pricing is available for groups.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBased on the information you provided, your team is eligible for a special discount, for Artificial Intelligence in Healthcare: Fundamentals and Applications starting on March 2, 2023 .
We’ve sent you an email with enrollment next steps. If you’re ready to enroll now, click the button below.
Have questions? Email us at group-enrollments@emeritus.org.AI plays an increasingly important role in patient treatments. With its ability to accurately predict diseases at early stages, AI is regarded as a powerful tool in today’s healthcare industry.
Since AI offers benefits such as informed patient care, improved patient safety, and innovative treatment options, it isn’t surprising that 56% of clinicians believe that most of their decisions over the next decade will be made using AI-based clinical decision support tools. However, clinicians face a knowledge gap and report the rising need for professionals who understand AI-based technologies and ways of leveraging them for the advantage of healthcare providers and patients.
With a focus on AI and its applications in modern-day healthcare, MIT xPRO’s AI in Healthcare: Fundamentals and Applications program is designed to give clinical leaders, healthcare IT professionals, and healthcare entrepreneurs the opportunity to learn how AI technologies can make a difference in patient treatment and enable them to develop innovative solutions to the healthcare challenges of today and tomorrow.
Healthcare technology is at a critical stage, and people with AI expertise have the power to determine its future.
The projected market size of AI-based global healthcare solutions by 2030
The increase in the number of U.S. hospitals that have implemented AI since 2020
The percentage of life sciences leaders who report a shortage of people with AI-implementation skills in their organization
Learn real-world application simulation by creating an AI decision framework relevant to healthcare
Gain an understanding of concepts and technologies, such as machine learning, deep learning, neural network NLP, and biomechatronics
Acquire insights and examples from expert MIT faculty
Develop your ability to assess challenges, opportunities, and future-driven patient care solutions involving a variety of AI technologies
Earn a certificate and four continuing education units (CEUs) from MIT xPRO
This program is designed to equip you with the skills to broaden your understanding of the applications of AI-based technologies in healthcare. The program will help you to:
This module focuses on the four stages of designing an AI product. You learn how to identify the desired AI behavior, assess business and technical requirements, measure value, and generate a software development plan. In addition, you learn how to identify the long-term advantages of a product and analyze the three types of AI cancers and their impact.
This module focuses on machine learning. You learn about the various algorithms, classifiers, decision trees (along with the advantages of training), and validation and testing sets. This module also shows you how to easily identify the best algorithms for different applications.
This module examines deep learning. It covers neural networks in depth as well as their applications in drug discovery and cancer research. You learn to run implementations on convolutions and deep and recurrent neural network algorithms while gaining an understanding of Python and artificial neurons.
Acquire a 360º approach to design with an understanding of superhuman targets, software methodologies, tool development, research, ethical responsibilities, and possible challenges to these applications. Learn about the COUHES/IRB approval processes, formulate crowdsourcing data strategies, and understand the extraordinary intelligence used in AI products and services.
The peloton framework has helped facilitate applications such as modern ingestible robots. You gain a thorough understanding of this framework and develop your own ideas for ingestible robots to help solve healthcare problems.
Deep dive into advanced prosthetics, proprioception, prosthetics, and exoskeletons. Understand their history, research, development, and current limitations, and learn how communication is crucial for the development of some of them.
Identify the immediate challenges and possibilities in the field of healthcare technologies, including business applications, maintenance challenges, various sources of inspiration, the potentials of electromagnetic waves, and the use of RFID chips. In addition, you design and develop an AI product for healthcare.
This module focuses on the four stages of designing an AI product. You learn how to identify the desired AI behavior, assess business and technical requirements, measure value, and generate a software development plan. In addition, you learn how to identify the long-term advantages of a product and analyze the three types of AI cancers and their impact.
The peloton framework has helped facilitate applications such as modern ingestible robots. You gain a thorough understanding of this framework and develop your own ideas for ingestible robots to help solve healthcare problems.
This module focuses on machine learning. You learn about the various algorithms, classifiers, decision trees (along with the advantages of training), and validation and testing sets. This module also shows you how to easily identify the best algorithms for different applications.
Deep dive into advanced prosthetics, proprioception, prosthetics, and exoskeletons. Understand their history, research, development, and current limitations, and learn how communication is crucial for the development of some of them.
This module examines deep learning. It covers neural networks in depth as well as their applications in drug discovery and cancer research. You learn to run implementations on convolutions and deep and recurrent neural network algorithms while gaining an understanding of Python and artificial neurons.
Identify the immediate challenges and possibilities in the field of healthcare technologies, including business applications, maintenance challenges, various sources of inspiration, the potentials of electromagnetic waves, and the use of RFID chips. In addition, you design and develop an AI product for healthcare.
Acquire a 360º approach to design with an understanding of superhuman targets, software methodologies, tool development, research, ethical responsibilities, and possible challenges to these applications. Learn about the COUHES/IRB approval processes, formulate crowdsourcing data strategies, and understand the extraordinary intelligence used in AI products and services.
Through this research, identify how to generate realistic-looking images of the heart that can be instrumental for cardiologists in diagnoses and treatment.
From this research, you learn about “Gencode”—the attempt at creating an encyclopedia of genes and genetic variants.
This research contains a useful tool for antibiotic discovery that can aid you in your own drug discovery.
Through this research, learn how to use an image-based, deep learning model that can predict breast cancer up to five years in advance.
From this research, you learn how to create bionic limbs that emulate the function of natural limbs.
From this case study, you learn how the instrument named Emerald functions. It measures sleep stages, gait speed and mobility, human pose estimation, and adherence.
From this research, learn how Bruce Lawler makes great strides in his goal to find the shortest path from data to impact.
Bruce Lawler
Brian Subirana
Duane Boning
Bruce Lawler
Managing Director, MIT Machine Intelligence for Manufacturing and Operations (MIMO)
Bruce Lawler is a technology entrepreneur and an executive leader. He has developed several applications across platforms, such as mobile, SaaS, AI, and video distribution networks. He has headed multiple ventures in fields ranging from consumer and industrial hardware to wireless and video network operations. As the managing director of MIT MIMO, Lawler focuses on resolving the data and operational challenges in manufacturing with measurable and impactful efficiency and revenue improvement.
Professor Lawler earned his bachelor’s in engineering at Purdue University and his master’s in engineering and MBA at MIT Sloan School of Management.
Brian Subirana
Former Director of MIT Auto-ID lab, MIT
Brian Subirana has taught at MIT Sloan and the MIT School of Engineering and is also the former director of the MIT Auto-ID lab and director of the MIT and Accenture Convergence Initiative for Industry and Technology. He is the faculty director for this program. His research centers on IoT and AI and focuses on manufacturing, e-learning, the creative industries, and digital health. He is developing a voice name system that can help humans talk to any object in an IoT environment. He has over 200 publications, including three books, and is currently researching open standards for AI and IoT.
Professor Subirana earned his doctorate in computer vision at the MIT Artificial Intelligence Laboratory (now CSAIL) and his MBA at MIT Sloan.
Duane Boning
Clarence J. Lebel Professor, Electrical Engineering and Computer Science
Duane Boning is affiliated with the MIT Microsystems Technology Laboratories and serves as associate director of machine learning and statistical methods for modeling and control of variation in manufacturing. His work is centered on statistical characterization and design for the manufacture of devices and circuits in advanced technologies as well as on the modeling of chemical and mechanical polishing, spin-on coatings, plasma etching, and nano-imprinting/embossing processes. His work has appeared in over 280 journals and conference publications.
Professor Boning earned his bachelor’s and master’s degrees in science and his doctorate in electrical engineering and computer science at MIT.
Upon successful completion of this program, MIT xPRO grants a certificate of completion to participants as well as four continuing education units (CEUs). This program is graded as a pass or fail; participants must receive 75% to pass and obtain the certificate of completion.
Download BrochureAfter the successful completion of the program, your verified digital certificate will be emailed to you, at no additional cost, in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of MIT xPRO.
Flexible payment options available.
