Machine learning for optimized intraoperative multiplexed quantitative optical image guidance for brain tumor surgeryĭirector, Image-Guided Neurosurgery, BH Professor, Neurosurgery, Radiology, HMSĭeepROP - a point-of-care system for diagnosis of plus disease in retinopathy of prematurityĭirector, QTIM Lab, MGH Associate Professor, Radiology, HMSīreast cancer scanning initiative: predicting unnecessary surgeries in high-risk-breast lesionsĪssociate Director, Center for Integrated Diagnostics, MGH Assistant Professor, HMS Vice President, Perioperative Services and Healthcare System Engineering, MGH Assistant Professor, Anesthesia, HMSĪ web-based neural network calculator for ovarian cancer screening using serum miRNAĭirector, Gynecologic Oncology Research Laboratory, BH Assistant Professor, HMS Using deep learning to predict next-day patient discharges to optimize hospital capacity management Live pilot test of an artificial intelligence system for trauma care decision-supportįinding needles in the haystack, using machine learning and natural language processing to identify patients and track disease progressionĪssociate Professor/Lead Investigator, BH Associate Professor, HMS Virtual biopsy of brain injury: deep learning to identify diagnostic metabolic biomarkersĭirector, Center for Clinical Spectroscopy, BH Assistant Professor, Radiology, HMSĪutomatic cerebral lesion detection and disease progression in patients with Adrenoleukodystrophy (ALD)Ĭo-Director Pediatric Cerebrovascular Service, MGH Assistant of Neurology, HMSĭisease-specific testing of an artificial intelligence system for tight blood pressure controlĭirector, Clinical Decision Technology Laboratory, MGH Associate Professor, Emergency Medicine, HMS Hostetter MGH Research Scholar, MGH Associate Professor, Radiology, HMS Making the 'invisible' visible: bringing intimate partner violence into focusĭirector, Emergency Musculoskeletal Radiology, BH Assistant Professor, HMSĭeveloping a novel machine learning algorithm to automate drug infusions in the operating room and ICUĪttending Anesthesiologist, BH Instructor, Anesthesiology, HMSĪrtificial Intelligence Diffraction Analysis (AIDA) IVF Laboratory Director, MGH Instructor, HMSĪ generalizable artificial intelligence platform for brain cancer frozen section diagnosisĬhair, Department of Pathology, BH Ramzi S. Questions related to the business opportunity should be directed to your Mass General Brigham Innovation Licensing Manager or Market Sector Leader at 85.Ĭomputational and experimental deconvolution of circulating exosomal signals in melanoma immunotherapy patientsĪssistant Professor of Surgery, Surgery, MGHĮmbryo assessment and selection using artificial intelligence Questions related to IDG grants policies or procedures should be directed Lesley Watts, Director of Sponsored Programs at / 85. Questions related to intellectual property and confidentiality should be directed to your Mass General Brigham Innovation Licensing Manager at 85. External pharma and device companies will be actively involved during the review process.ĭo not include unprotected proprietary information in your application. Guidelines and further information are available on the opportunity website: Īwards will be governed by the Mass General Brigham Intellectual Property Policy.Project plans must demonstrate tangible outcomes towards commercialization opportunities that improve patient health or healthcare delivery.Projects may request up to $100,000 total cost (inclusive of 15% indirect costs).The earliest possible start date is June 1st, 2022.
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Full proposals will be due February 1, 2022, 11:59pm EST.Full proposals will be invited by December 17, 2021.
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