Accession Number:

AD1168004

Title:

Diversity-Promoting and Large-Scale Machine Learning for Healthcare

Descriptive Note:

[Technical Report, Doctoral Thesis]

Corporate Author:

Carnegie Mellon University

Personal Author(s):

• Xie, Pengtao

Report Date:

2018-08-01

Pagination or Media Count:

258

Abstract:

In healthcare, a tsunami of medical data has emerged, including electronic health records, images, literature, etc. These data are heterogeneous and noisy, which renders clinical decision-makings time-consuming, error-prone, and suboptimal. In this thesis, we develop machine learning ML models and systems for distilling high value patterns from unstructured clinical data and making informed and real-time medical predictions and recommendations, to aid physicians in improving the efficiency of workflow and the quality of patient care.

Descriptors:

• health services
• computational science
• medical personnel
• data mining
• bayesian networks
• information science
• network science
• neural networks
• artificial intelligence software
• ontologies
• information processing
• computer languages
• automata theory
• computer vision
• machine learning
• information systems

Subject Categories:

• Numerical Mathematics
• Administration and Management
• Cybernetics

Distribution Statement:

[A, Approved For Public Release]