With artificial intelligence permeating more aspects of healthcare and research, the Cedars-Sinai Graduate School of Biomedical Sciences is launching a doctoral program. program focused on healthcare AI.
The Los Angeles-based program is designed to equip students with cutting-edge artificial intelligence algorithms, emphasizing clinical data analysis to inform patient care. Through active learning, clinical rotations, and collaboration with clinicians, our program ensures that graduates are prepared to navigate and contribute to the dynamic world of AI in medical research and patient well-being.
The curriculum of the Ph.D. The AI in Health program, which is pending accreditation, emphasizes an active learning approach that will be used to deliver six required courses, including AI, ethical AI, machine learning, natural language processing, clinical applications of AI, and computer science. biomedical. Students will gain healthcare experience through clinical rotations, clinical collaborations, and access to electronic medical record clinical data.
The program is directed by Graciela González-Hernández, Ph.D., vice president of research and education in the Department of Computational Biomedicine. “The Cedars-Sinai PhD in Artificial Intelligence in Health program is designed around a student-centered philosophy: you bring your own knowledge, past experiences, education and ideas, and discover with us how to expand them in new and exciting directions “, said. in a sentence. “You will have the unique opportunity to work alongside world-renowned experts in artificial intelligence and healthcare, directly interacting with cutting-edge technologies that are shaping the future of medicine. “Our program emphasizes developing practical skills and solving real-world problems, ensuring you are not only prepared to excel in your career but also to lead and innovate.”
This program will provide doctoral students with the knowledge and practical experience to develop, evaluate, and apply AI algorithms and methods to improve patient care.
Students will be exposed to hospital rotations to better understand how AI could be used in healthcare. Students will work with clinical collaborators and have access to electronic health record data. Graduates of the program will be positioned to improve healthcare and patient outcomes through the rigorous development and implementation of artificial intelligence algorithms and software, Cedars-Sinai said.
The study plan includes:
• Computational Biomedicine: This course will provide a broad introduction to the field of computational biomedicine, including the analysis, interpretation, and use of biomedical and clinical data to improve patient care.
• Artificial intelligence: This course will cover fundamental concepts of artificial intelligence, including history, logic, semantics, knowledge engineering, rule-based learning, probability, search, and machine learning.
• Ethical Artificial Intelligence: This course will present and discuss the ethical issues associated with applying artificial intelligence methods to clinical data and deploying artificial intelligence in the clinic for patient care.
• Machine learning: This course will cover key concepts and methods in machine learning, including feature selection, feature engineering, model selection, prediction, evaluation, and interpretation.
• Natural language processing: This course will introduce algorithms, methods, and software for text and language processing.
• Clinical Artificial Intelligence: This course will present and discuss the challenges and opportunities of using artificial intelligence for patient care with practical examples and use cases.
• Electives: The student will select two electives to provide a specialization or focus. Examples include biostatistics, computational biology, and image analysis.
All students must complete a minimum of 20 hours of clinical rotations in one or more specialties. During these rotations, students will shadow physicians during patient encounters and observe interactions, using electronic medical records and decision support tools.
All students will also complete three rotations during the first year in candidate thesis research laboratories. This process will culminate in the identification of a research mentor willing to supervise a thesis research project.
Students are expected to conduct a thesis research project that generates new knowledge at the intersection of AI and healthcare. The project will facilitate collaboration between AI experts and clinicians, culminating in several peer-reviewed publications.
The program’s faculty is comprised of experienced educators and leading experts in artificial intelligence, bioinformatics, biomedical informatics, biostatistics, computational biology, epidemiology, machine learning, and natural language processing.
