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Digital Health Care 0418 RESEARCH SURVEY Digital Health Care Big data, clinical decision-making, health information systems, machine learning, predic- tion, mobile diagnostic tools, implantable, ingestible, wireless devices, sensors... Digital Health Care: Clinical Decision-Making, Machine Learning, Mobile Diagnostic Tools, Ingestible, Wearable Devices, etc. This survey by MIT’s Industrial Liaison Program identifies selected research and expertise in digital health care related to clinical decision-making, data, machine learning, mobile diagnostic tools, and implantable/ingestible and wearable devices, etc. For more information, please contact MIT’s Industrial Liaison Program at +1-617-253-2691. BIG DATA, CLINICAL DECISION-MAKING, HEALTH INFORMATION SYSTEMS, MACHINE LEARNING, PREDICTION ............................................................................................................................... 6 REGINA BARZILAY ............................................................................................................................................. 6 Learning to Cure ............................................................................................................................................ 6 High-risk breast lesions: A machine learning model to predict pathologic upgrade and reduce unnecessary surgical excision............................................................................................................................................. 6 Using artificial intelligence to improve early breast cancer detection ............................................................................. 7 Machine learning to parse breast pathology reports in Chinese....................................................................... 8 Using machine learning to parse breast pathology reports .............................................................................. 8 DIMITRIS J BERTSIMAS ....................................................................................................................................... 9 Algorithmic Approaches to Personalized Health Care ..................................................................................... 9 Optimal healthcare decision making under multiple mathematical models: application in prostate cancer screening.......................................................................................................................................................10 Accept or Decline? An Analytics-Based Decision Tool for Kidney Offer Evaluation .......................................10 Personalized diabetes management using electronic medical records .............................................................11 Transforming decision making with analytics .................................................................................................11 POLINA GOLLAND..............................................................................................................................................11 Cardiac MRI analysis ....................................................................................................................................12 Clinical Neuroimaging ..................................................................................................................................12 Monitoring Fetal Health ................................................................................................................................12 Fast geodesic regression for population-based image analysis .......................................................................12 Population based image imputation ...............................................................................................................13 New technique makes brain scans better ...................................................................................................................... 13 Video: Making Invisible Obvious: Computational Analysis of Medical Images ...............................................14 Temporal Registration in In-Utero Volumetric MRI Time Series .....................................................................14 MRIs for fetal health................................................................................................................................................... 14 JOHN V. GUTTAG ...............................................................................................................................................15 Data-Driven Inference Group ........................................................................................................................15 Hidden Influencers, Risk and Causes of Infection ........................................................................................................ 15 Predicting Adverse Events Across Changing Electronic Health Record Systems ........................................................... 16 Video: Transforming Healthcare Using Machine Learning ............................................................................16 Predicting clinical outcomes across changing electronic health record systems ..............................................16 Using machine learning to improve patient care ........................................................................................................... 17 THOMAS HELDT.................................................................................................................................................17 Computational Physiology and Clinical Inference Group (CPCI) ...................................................................18 Integrating Data, Models, and Reasoning in Critical Care ............................................................................................ 18 MIT Industrial Liaison Program April 2018 | Page 2 Model-Based Estimation of Respiratory Parameters from Capnography, with Application to Diagnosing Obstructive Lung Disease ..............................................................................................................................19 Prediction of postoperative outcomes using intraoperative hemodynamic monitoring data .............................19 MIT Professional Education Course: Quantitative Cardiorespiratory Physiology and Clinical Applications For Engineers (June 2018) ............................................................................................................................20 UNA-MAY O'REILLY .........................................................................................................................................20 Anyscale Learning for All (ALFA) Group .......................................................................................................21 GIGABEATS: Data science for medical sensor data .................................................................................................... 21 BeatDB v3: A Framework for the Creation of Predictive Datasets from Physiological Signals ........................21 Analysis of locality-sensitive hashing for fast critical event prediction on physiological time series.................22 ROSALIND W. PICARD ........................................................................................................................................22 Affective Computing Research Group ............................................................................................................23 Machine Learning for Pain Measurement .................................................................................................................... 23 Behavioral Indications of Depression Severity ............................................................................................................. 23 Automated Tongue Analysis ....................................................................................................................................... 23 Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health ..................................23 Personalized Automatic Estimation of Self-Reported Pain Intensity from Facial Expressions ..........................24 Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors ......................24 Wrist sensor reveals sympathetic hyperactivity and hypoventilation before probable SUDEP .........................25 BrightBeat: Effortlessly influencing breathing for cultivating calmness and focus ...........................................25 DAVID SONTAG .................................................................................................................................................25 Clinical Machine Learning Group .................................................................................................................26 Precision Medicine ..................................................................................................................................................... 26 Intelligent Electronic Health Records .......................................................................................................................... 26 Learning a Health Knowledge Graph from Electronic Medical Records .........................................................27 Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning ...........................................................................................................................................27
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