AI in Healthcare Capstone from Coursera

This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider. We will follow the patient's journey from the lens of the data that are created at each encounter, which will bring us to a unique de-identified dataset created specially for this specialization. The data set spans EHR as well as image data and using this dataset, we will build models that enable risk-stratification decisions for our patient. We will review how the different choices you make -- such as those around feature construction, the data types to use, how the model evaluation is set up and how you handle the patient timeline -- affect the care that would be recommended by the model. During this exploration, we will also discuss the regulatory as well as ethical issues that come up as we attempt to use AI to help us make better care decisions for our patient. This course will be a hands-on experience in the day of a medical data miner.

In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.

What's inside

Syllabus

Getting Started, Phase 1: Data Collection

Phase 2: Model Training Part 1

Phase 3: Model Training Part 2

Phase 4: Model Evaluation

Phase 5: Model Deployment and Regulation, Wrap Up

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

This course explores a diverse set of concepts that are standard in the practice of medical data mining

Taught by recognized experts in the medical data mining field, this course provides access to a wealth of knowledge

Develops an in-depth understanding of relevant healthcare data, which is a core skill for medical data miners

Examines regulatory and ethical issues that arise in the use of AI in healthcare, providing valuable insights for practitioners

Offers hands-on experience in medical data mining, providing learners with practical skills

Extension of the Learning Health System program, which is recognized for its excellence

Reviews summary

Ai in healthcare capstone: comprehensive and engaging

Learners say the AI in Healthcare Capstone course is an engaging, well-structured course that provides a broad coverage of AI in Healthcare. The peer review component is a valuable feature, and the in-depth learning is appreciated. Reviewers also recommend having a strong technical foundation before taking this course. Overall, this course is highly recommended for those interested in the field of AI in Healthcare.

Thoughtful and constructive peer feedback.

"The quality of peer review exercises was good and the content of the reading material was well understood"

"Really enjoy the Capstone projects with wonderful peer-reviewing."

"Getting AI specialization Stanford University is very amazing and effective to start your AI careers."

Thorough coverage of AI in Healthcare.

"Amazing experience, such in depth learning to understand how to approach data problems in healthcare settings and where they can actually be of benefit."

"Excellent introduction to the field of 'AI in medicine'."

"The course covers diverse topics and need very deep knowledge of Machine Learning and AI"

Captivating and interactive experience.

"Nicely Framed and Executed in a simple language so anyone can catch up earliest."

"Really enjoy the Capstone projects with wonderful peer-reviewing."

"I really enjoyed this course as it was applied learning of all I learned during the previous courses of the specialization."

Minor technical issues and grading mistakes.

"Some technical issues with the quizzes and assignments (ie one assignment had no question, just an answer)."

"I was disappointed with the quality of the submissions I saw and the wording of some the quizzes, which in many cases had questions which were incorrectly scored or graded."

Prior knowledge in AI recommended.

"Some technical issues with the quizzes and assignments (ie one assignment had no question, just an answer)."

"Although I have some differences in the approach chosen by the instructors on some topics such as bias, the material is invaluable."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AI in Healthcare Capstone with these activities:

AI in Medicine

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Prepare by brushing up on the latest advancements in artificial intelligence, its applications in medicine, and the relevant ethical considerations.

Browse courses on AI in Healthcare

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Read journal articles
Watch online lectures
Attend a webinar

Group Discussion Forum

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Engage with peers by participating in online discussion forums to exchange insights and deepen your understanding of course concepts.

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Join a discussion forum
Post thoughtful questions
Respond to other participants

Peer Mentorship

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Deepen your understanding by mentoring a fellow student and providing guidance on course concepts and assignments.

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Identify a mentee
Establish a regular meeting schedule
Provide support and guidance

Four other activities

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Organize Course Notes

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Reinforce your understanding by organizing and reviewing your lecture notes, assignments, and quizzes.

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Create a filing system
Summarize key concepts
Review materials regularly

AI for Healthcare Workshop

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Attend a workshop to gain hands-on experience in applying AI techniques to real-world healthcare data.

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Find a relevant workshop
Register and attend the workshop
Participate actively

Coding Challenges

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Solidify your coding skills by solving coding challenges related to medical data analysis and modeling.

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Find online coding challenges
Participate in coding competitions
Build a portfolio of coding projects

Advanced Machine Learning Techniques

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Expand your knowledge by exploring advanced machine learning techniques and their applications in medical data analysis.

Browse courses on Machine Learning Algorithms

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Identify relevant tutorials
Complete tutorials
Apply techniques to your own projects

Career center

Learners who complete AI in Healthcare Capstone will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. The AI in Healthcare Capstone course provides a solid foundation in data collection, model training, and evaluation, all of which are essential skills for a Data Scientist in the healthcare industry. The course also covers regulatory and ethical issues in using AI in healthcare, which is a critical consideration for professionals working in this field.

See salaries and explore the career path for Data Scientist

Healthcare Data Analyst

A Healthcare Data Analyst collects, analyzes, and interprets healthcare data to identify trends, patterns, and insights. The AI in Healthcare Capstone course provides a foundation in healthcare data analysis, including data collection, data cleaning, and data visualization. The course also covers specific applications of AI in healthcare, such as risk stratification and disease prediction.

See salaries and explore the career path for Healthcare Data Analyst

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models to solve real-world problems. The AI in Healthcare Capstone course provides hands-on experience in building machine learning models for healthcare applications. The course covers topics such as feature engineering, model selection, and evaluation, which are essential for a Machine Learning Engineer working in the healthcare industry.

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Medical Doctor

A Medical Doctor diagnoses and treats diseases and injuries. The AI in Healthcare Capstone course provides insights into the use of AI in healthcare, which can help Medical Doctors stay up-to-date on the latest advancements in medical technology. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Medical Doctors who are using or considering using AI in their practice.

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Pharmacist

A Pharmacist dispenses medications and provides advice on their use. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Pharmacists stay up-to-date on the latest advancements in pharmacy practice. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Pharmacists who are using or considering using AI in their practice.

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Health Informatics Specialist

A Health Informatics Specialist designs, develops, and implements health information systems. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Health Informatics Specialists stay up-to-date on the latest advancements in health information technology. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Health Informatics Specialists who are responsible for ensuring the safe and ethical use of AI in health information systems.

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Epidemiologist

An Epidemiologist investigates the distribution and determinants of health-related states or events in a population. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Epidemiologists stay up-to-date on the latest advancements in epidemiological methods. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Epidemiologists who are using or considering using AI in their research.

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Biostatistician

A Biostatistician uses statistical methods to design, analyze, and interpret data from medical and health research studies. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Biostatisticians stay up-to-date on the latest advancements in statistical methods. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Biostatisticians who are using or considering using AI in their research.

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Healthcare Administrator

A Healthcare Administrator plans, organizes, and manages the delivery of healthcare services. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Healthcare Administrators make informed decisions about using AI in their organizations. The course also covers the ethical and regulatory implications of AI in healthcare, which is important for Healthcare Administrators who are responsible for ensuring the safe and ethical use of AI in their organizations.

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Medical Writer

A Medical Writer creates and edits medical content, including scientific papers, journal articles, and patient education materials. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Medical Writers stay up-to-date on the latest advancements in medical technology. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Medical Writers who are creating content about the use of AI in healthcare.

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Clinical Research Coordinator

A Clinical Research Coordinator assists in the design, implementation, and management of clinical research studies. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare research, which can help Clinical Research Coordinators stay up-to-date on the latest advancements in research methods. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Clinical Research Coordinators who are responsible for ensuring the safe and ethical conduct of clinical research studies.

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Health Policy Analyst

A Health Policy Analyst analyzes and evaluates health policies and programs. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Health Policy Analysts stay up-to-date on the latest advancements in healthcare policy. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Health Policy Analysts who are responsible for developing and implementing health policies.

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Healthcare Consultant

A Healthcare Consultant provides advice and guidance to healthcare organizations on a variety of topics, including the use of AI. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Healthcare Consultants stay up-to-date on the latest advancements in healthcare technology. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Healthcare Consultants who are advising healthcare organizations on the use of AI.

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Social Worker

A Social Worker provides support and guidance to individuals and families facing challenges. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Social Workers stay up-to-date on the latest advancements in social work practice. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Social Workers who are using or considering using AI in their practice.

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Nurse

A Nurse provides direct patient care and education. The AI in Healthcare Capstone course provides an overview of the use of AI in healthcare, which can help Nurses stay up-to-date on the latest advancements in nursing practice. The course also covers ethical and regulatory issues related to AI in healthcare, which is important for Nurses who are using or considering using AI in their practice.

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