Covers recent advances in data management systems. Topics include complex queries and optimizations, XML data management, spatial data management, distributed and parallel databases, NoSQL databases, and MapReduce based data processing systems. Discusses foundations of data models, transaction models, storage, indexing and querying methods.
Introduces students to the fundamentals of computer science and Python programming with a focus on solving problems in biomedical informatics. Students will learn to write, interpret, and modify code, analyze biomedical data, and explore real-world biomedical applications.
Introduces students to imperative programming language concepts using C. Covers variables, data types, expressions, functions, control-flow constructs, and writing safe and modular programs. No prior programming experience required.
The design of database applications including Entity-Relationship data modeling, the relational data model, SQL, application development, and database administration. Students complete a project designing and implementing a database application.
Covers fundamentals of biomedical informatics including Electronic Health Records, biomedical and healthcare data management and standards, medical imaging informatics, medical image analysis, bioinformatics, and public health informatics and GIS.
A multidisciplinary field intersecting clinical informatics, medical physics, engineering, computer and information sciences. Covers the whole imaging chain: image creation and acquisition, distribution and management, storage and retrieval, processing and analysis, visualization and interpretation. Topics include radiological imaging modalities, DICOM standards, PACS systems, digital pathology, and emerging technologies in Imaging Informatics.