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CSAIL, MIT, computer science, natural language processing, medical engineering


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Health Care of the Future

The Clinical Decision Making Group at MIT's Computer Science and Artificial Intelligence Laboratory, led by Professor Peter Szolovits, is dedicated to using natural language processing techniques to make better sense of unstructured medical records.

William Long, a principal research scientist in the Clinical Decision Making Group, has developed several programs that scan through pages of electronic nurses reports and ICU discharge summaries, searching for keywords and phrases that provide clues to a patient's condition. Relying on information gathered from the Uniform Medical Language System, a compilation of over 150 medical dictionaries, the Clinical Decision Making Group has programmed the system to identify a comprehensive list of terms and key concepts.

Thus far, this technology has been used more for clinical research than diagnostic purposes. For example, the technology has been used to gather a group of patients who are all suffering from the same medical condition, but who reacted differently to identical treatment methods. Thanks to systems that can organize and parse medical records, physicians can uncover whether genetics, outside medications or personal habits affected the patient, and learn more about which treatments are, and are not, effective.

Szolovits still believes in applying artificial intelligence to the diagnostic process, but in a different manner than originally envisioned. In collaboration with Dr. Roger Mark and Dr. George Verghese, a collaborative group including CSAIL, LIDS, HST and the BIDMC has collected data on approximately 35,000 ICU admissions to a major Boston hospital. CSAIL graduate Caleb Hug used the data to create predictive models that estimate, each time something significant changes in a patient's state, how they are likely to fare in the future. Such acuity models can warn clinicians of danger and are also useful in determining the resources needed to assist a particular patient.


Peter Szolovits (Massachusetts Institute of Technology)
William Long (Massachusetts Institute of Technology)

Institution(s) (that have supported the research):
MIT Computer Science and Artificial Intelligence Laboratory


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