We’re excited to announce that Dr. Tim Miller, assistant professor on the Harvard Medical School (link), and college member within the Computational Health Informatics Program (link) at Boston Children’s Hospital, has joined the Lavita advisory council.

Prof. Miller is PI(Principal Investigator) of the Machine Learning for Medical Language lab at Harvard Medical School. His research is devoted to developing recent algorithms for natural language processing (NLP) of clinical text, with the aim of extracting vital information from health-related texts to streamline clinical research and make healthcare systems more efficient. His lab has funded projects specializing in the vital problems of domain adaptation for clinical NLP, and learning patient representations from electronic health records. Prof.. Miller accomplished his PhD in Computer Science at University of Minnesota.

Prof. Miller’s work in the sector of clinical NLP has covered a broad array of applications (link), from clinical research-enabling phenotyping applications, to semantic processing of clinical texts, to core contributions to NLP and machine learning. He has developed techniques for syntactic contributions in temporal relation extraction and has significantly contributed open source projects Apache cTAKES (clinical Text Evaluation and Knowledge Extraction System)

The ever-growing volume of health-related texts, equivalent to electronic health records, clinical trial reports, and scientific literature, holds a wealth of invaluable information that may revolutionize healthcare and clinical research. One of the crucial promising ways to unlock this potential is through the use of AI and NLP technologies to extract vital information from these texts, ultimately streamlining clinical research and increasing healthcare system efficiency.

Within the context of clinical research, NLP may also help researchers quickly and accurately extract relevant information from vast amounts of knowledge. This process can significantly speed up the evaluation and synthesis of information, resulting in faster discoveries and more efficient clinical trials. By automating the extraction of data from clinical trial reports, scientific articles, and other health-related texts, researchers can spend more time on hypothesis generation, experimental design, and data interpretation.

We’re fortunate to work with Prof. Miller as our advisor. Together with his expertise on board, Lavita is poised for continued growth and innovation in its first-of-a-kind patient-driven health information marketplace. Prof. Miller’s knowledge, experience, and keenness in clinical NLP will contribute to Lavita’s vision of revolutionizing the way in which individuals around the globe manage, share, and utilize their health data, enabling higher access to healthcare services and improving patients’ lives.