Courses Taught by Rahul Ladhania

HMP637: Artificial Intelligence For Health Care Policy

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Rahul Ladhania (Residential);
  • Prerequisites: None
  • Description: Understand the role of AI and machine learning in healthcare and policy, focusing on opportunities, limitations, and real-world applications. Through case studies, discussions, projects, and speaker sessions, students will gain a nuanced understanding of AI’s role in healthcare transformation, complemented by exposure to relevant programming tools.
  • Learning Objectives: Get a basic understanding of application of Machine Learning techniques: Identify key machine learning methods, understand their application in healthcare delivery, clinical decision-making, and risk prediction, and apply these techniques to health data - Critically Evaluate AI/ML in Healthcare: Analyze and critique the use of AI/ML in various domains of healthcare and health policy, understanding both its potential benefits and limitations. - Address Ethical and Social Implications: Evaluate the fairness, bias, and privacy concerns in AI applications, and understand the ethical and policy considerations relevant to healthcare - Gain introductory exposure to data analysis tools: Develop basic proficiency in using features of programming tools such as R to apply to relevant health data problems - Engage in Professional Development through Invited Guests and Project Work: Collaborate on a group project that explores a pressing AI/health policy topic, incorporating a data analysis component, and presenting findings through both written and oral presentations - Communicate Effectively in AI and Health Policy Contexts: Communicate complex AI/ML concepts clearly to both technical and non-technical audiences, and participate effectively in discussions around AI’s impact on healthcare.
LadhaniaRahul
Rahul Ladhania

HMP669: Data Management And Visualization In Healthcare

  • Graduate level
  • Both Residential and Online MPH
  • This is a second year course for Online students
  • Winter term(s) for residential students; Winter term(s) for online MPH students;
  • 1.5-3 credit hour(s) for residential students; 3 credit hour(s) for online MPH students;
  • Instructor(s): Rahul Ladhania (Residential); Rahul Ladhania (Online MPH);
  • Prerequisites: None
  • Advisory Prerequisites: Graduate Standing
  • Description: This course is an introduction to the use of relational databases and data visualization tools for decision-making. It covers: A. design and implementation of, and data retrieval from, small-to-medium relational database systems using Microsoft Access; and B. data manipulation, analysis and visualization using the R programming language.
  • Residential Syllabus for HMP669
LadhaniaRahul
Rahul Ladhania

HMP681: Special Topics in Health Management and Policy

  • Graduate level
  • Residential
  • Fall, Winter term(s) for residential students;
  • 1-3 credit hour(s) for residential students;
  • Instructor(s): April Zeoli, Rahul Ladhania, Richard Hirth, Matthew Comstock, (Residential);
  • Prerequisites: None
  • Undergraduates are allowed to enroll in this course.
  • Description: Lecture, seminars and readings selected on a current or emerging topic or theme in health, management and policy. The specific material and format will vary by semester and instructor.
  • Learning Objectives: Will vary by topic and instructor.
ZeoliApril
April Zeoli
LadhaniaRahul
Rahul Ladhania
HirthRichard
Richard Hirth
ComstockMatthew
Matthew Comstock