In-person social networkwebsite, TEDx, press
An average person spends two hours a day on social media, but almost half of us eat lunch alone. We created Connect to solve that problem. Since its creation in 2015, we have arranged nearly 10,000 platonic, in-person connections between students, alumni and staff at university campuses across the United States.
Coma prognosticationEMBC'15, NCS'16, ACNS'17, Thesis (slides)
Cardiac arrest impacts over half a million people a year. Even if successfully resuscitated, patients can enter an indefinite coma. Predicting if patients will wake up from coma can prevent premature withdraw of care. We compiled the world's largest dataset of Electroencephelograms (EEG) from patients in coma after cardiac arrest, and built advanced algorithms that use EEG to rapidly predict coma outcomes.
Personalized medication dosingICM'14, EMBS'16, AAAI'18 (slides)
Mis-dosing sensitive medications can have dire consequences for patient care. We developed a personalized medication dosing algoithm that is robust to missing data, a common problem in intensive care settings. The approach was 29% more accurate than intensive care staff, and better able to distinguish outcomes than non-personalized models.
Digitizing paper recordsBigData'17 (slides, code)
Clinical researchers, historians, educators and field researchers regularly capture data on paper spreadsheets. We built a tool that transcribes images of paper-based spreadsheets into electronic form. The open-source tool provides a generalized solution for spreadsheet transcription that maintains privacy, is up to 10 times faster and twice as cost effective as existing alternatives.
Determining the mood of a storyAAAI'17 (slides, press, video)
Inferring the emotional content of a story requires consideration of para-linguistic cues (e.g. pitch), linguistic content (e.g. vocabulary) and the physiological state of the narrator (e.g. heart-rate). We developed an algorithm that combines real-time auditory, text, and physiological signals to predict the mood (happy or sad) of people narrating a story.
Provider seniment and resource utilizationEMBC'18 (poster, press) CinC'15 (slides)
Decisions about patient care, especially in the ICU, are complicated. Doctors consider an incredible number of factors (lifestyle habits, family history, severity of illness etc.) when deciding what exams to order, and what treatments to prescribe. But doctors aren't machines; In addition to signals, charts, and measurements, they also have "gut feelings" about their patients. We were curious if these gut feelings were measurable, and to what extent they had an impact on care decisions. To answer these questions we studied 10 years of medical data, collecting information on all the patient factors that influence doctor's care decisions: age, gender, disease type and severity etc. But we also quantified how the doctor's felt about their patients by performing a sentiment analysis on their written care notes. We discovered that the doctor's feelings about patient predicted their care decisions: when doctors were more pessimistic, they also tended to order more exams, independent of what the other factors were telling them.
Medical 'Big Data'Nature Scientific Data '16 ( data )
We provide a freely accessible, large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.
Biomarkers of schizophreniaFront Hum Neurosci.'12
Genetic factors contribute to the etiology of mental diseases, including schizophrenia. We developed a method to identify genetic variations associated with functional brain networks in schizophrenia. We found functional networks located in the thalamus, anterior and posterior cingulate gyri. The contributing genetic factors fell into two clusters centered at chromosome 7q21 and chromosome 5q35.
Mapping mental representationsCurr Biol. '13
Humans develop rich mental representations that guide their behavior in a variety of everyday tasks. We developed a novel method to extract these complex representations through simple tasks. The extracted distributions allow us to predict the behavior of subjects to novel stimuli.
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Copyright, Mohammad M. Ghassemi, 2017