Pedro Teixeira, MD, PhD
VP of AI Engineering @ Prompt Health
About
PredictionHealth's mission is to make healthcare awesome - faster. We're starting by processing millions of notes from every visit to help physical therapy organizations improve their compliance and coding efficiency. We're working to analyze unstructured data in real-time and incorporate AI for all patients to help prevent mistakes and improve outcomes. Better, easy to understand data can help us all improve! Interests include machine learning, natural language processing, and user interface design. Previous research leveraged machine learning and natural language processing to automate large-scale identification of phenotype-genotype associations within electronic medical record data.
United States
Nashville
Hospital & Health Care
Machine Learning, Medicine, Python, C++, Java, Natural Language Processing, Android Development, Molecular Biology, Immunohistochemistry, Algorithms, Genetics, Netezza, Databases, Parallel Computing, EMR data analysis, Phenotyping algorithms, Structural Bioinformatics, Correlation Analysis, Statistics, Computer Science
Experience
VP of AI Engineering
Prompt Health
Co-founder and CEO
PredictionHealth
Healthcare has a fundamental data problem. Clinicians hate documentation and the notes generated are difficult to use to track quality and apply machine learning. We generate structured documentation for clinicians so they can focus on taking care of patients and the dataset we generate is designed for machine learning applications to improve healthcare. Make healthcare awesome - faster.
MD/PhD Candidate
Vanderbilt University Medical Center
Wonderful people, excellent school, amazing department of biomedical informatics, one awesome decade of my life
Research Assistant
Harvard Medical School
New England Regional Manager
Ivy Insiders
Education
Vanderbilt University School of Medicine
Vanderbilt University
Biomedical Informatics
Computational phenotyping in the electronic health record - leveraging machine learning and natural language processing to identify hypertensive individuals and perform phenome-wide association scans
Harvard University
Biochemical Sciences/Computer Science
Vanderbilt University
Biomedical Informatics
Improved protein folding prediction by leveraging machine learning and novel amino acid site-site correlation measures
Pedro Teixeira, MD, PhD's Contact Information
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