Skip to main content

MIT Corporate Relations

MIT Corporate Relations
MIT Logo
  • Read
  • Watch
  • Attend
  • About
  • Connect
  • MIT Startup Exchange
Search
  • Sign-In
  • Register
MIT ILP Home
  • Read
    • Faculty Features
    • Research
    • News
  • Watch
  • Attend
    • Conferences
    • Webinars
    • Learning Opportunities
  • About
    • Membership
    • Staff
    • For Faculty
  • Connect
    • Faculty/Researchers
    • Program Directors
  • MIT Startup Exchange
User Menu and Search
  • Sign-In
  • Register
MIT ILP Home
Toggle menu
  • Sign-in
  • Register
  • Read
    • Faculty Features
    • Research
    • News
  • Watch
  • Attend
    • Conferences
    • Webinars
    • Learning Opportunities
  • About
    • Membership
    • Staff
    • For Faculty
  • Connect
    • Faculty/Researchers
    • Program Directors
  • MIT Startup Exchange

Search Results


Filter Results
  • Show:
  • 10
  • 50
  • 100

Filter Results

Narrow your results
  • News (275)
  • Videos (417)
  • Events (134)
  • Research (1064)
  • Faculty (312)
  • Members (1)
2219 search results found
  • Strategies for Managing Complex AI Systems: From Development to Deployment

    Strategies for Managing Complex AI Systems: From Development to Deployment

    Thu, November 4, 2021 Webinar
    MIT Professional Education Webinar

    AI is transforming many industries. But addressing the full cycle, from development through deployment, requires key system engineering building blocks. Without these frameworks, efforts can be costly and unsuccessful. Learn how an AI systems engineering approach can avoid implementation pitfalls in this live webinar—a preview of the upcoming live virtual course  AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment.

  • Publication date: December 2, 2014
    Books
    Didier Bonnet, Dr. George Westerman, Dr. Andrew P McAfee

    Leading Digital: Turning Technology into Business Transformation

  • December 6, 2006
    Department of Mechanical Engineering

    Digital Acoustic Telemetry

    Principal Investigator Arthur Baggeroer

  • January 8, 2007

    Bioelectrical Strategies for Image-Guided Therapies

    Principal Investigator Richard Cohen

  • December 12, 2014 MIT News

    More-flexible digital communication

  • SMR-Logo
    June 4, 2018

    Avoid These Five Digital Retailing Mistakes

  • Publication date: July 30, 2010
    Books
    Edited by Michael E. Brown, Sean M. Lynn-Jones and Steven E. Miller

    Contending with Terrorism: Roots, Strategies, and Responses

  • Conference-ICT-2018

    Daisy Zhuo - 2016-Digital-Health_Conf-videos

    September 14, 2016Conference Video Duration: 33:47

    Personalized Health Care

    We present an example of ongoing research in the space of analytics-driven personalized healthcare and showcase an example of a healthcare technology startup spun off of our research endeavor.

    The first part of the talk discusses an ongoing research work on personalized diabetes management. Current clinical guidelines for managing type 2 diabetes do not differentiate based on patient-specific factors. We present a data-driven approach for personalized diabetes management that improves health outcomes relative to the standard of care. We modeled outcomes under thirteen pharmacological therapies based on electronic medical records from 1999 to 2014 for 10,806 type 2 diabetes patients from Boston Medical Center. We developed a recommendation algorithm that prescribes a regimen if the expected improvement from switching regimens exceeds a threshold. For patient visits in which the algorithmic recommendation differed from the standard of care, the mean post-treatment glycated hemoglobin (HbA1c) under the algorithm was lower than standard of care by 0.44% +/- 0.03% (p << 001), from 8.37% under the standard of care to 7.93% under our algorithm. A personalized approach to diabetes management yielded substantial improvements in HbA1c outcomes relative to the standard of care. Our prototyped dashboard visualizing the recommendation algorithm can be used by providers to inform diabetes care and improve outcomes.

    The second part of the talk presents an overview of MyA Health, a spinoff based on similar research efforts aimed at personalizing health care down to the individual. MyA is powered by a wealth of data sources encompassing historical claims, electronic medical records, wellness and biometric data, wearable device records, and consumer lifestyle data. The backend of MyA is empowered by a high-dimensional analytics engine with: (1) a suite of predictive machine learning algorithms to predict future healthcare costs, disease progression and outcome variability; and (2) robust optimization algorithms to optimize and personalize healthcare decisions that will best mitigate an individual’s financial burden and maximize their healthcare outcomes. To the consumer, MyA is an individual’s healthcare advisor that personalizes decisions ranging from what health plan is best to cover their risk to what drug/treatment is likely to benefit them the most. MyA is unique in that it takes the totality of data sources available to make personalized recommendations, a concept that is made possible given the healthcare data digitization revolution and the increasing adoption of wearable wellness and health monitoring devices.

    2016 MIT Digital Health Conference

  • Publication date: October 23, 2017
    Books
    By MIT Sloan Management Review

    How to Go Digital: Practical Wisdom to Help Drive Your Organization's Digital Transformation

  • January 15, 2016
    Abdul Latif Jameel World Education Lab (J-WEL)

    Digital Organization: How Fast-Moving Digital Innovations are Changing the Way We Work and Manage

    Principal Investigator George Westerman

Pagination

  • of 222
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30
  • 31
  • 32
  • 33
  • 34
  • 35
  • 36
  • 37
  • 38
  • 39
  • 40
  • 41
  • 42
  • 43
  • 44
  • 45
  • 46
  • 47
  • 48
  • 49
  • 50
  • 51
  • 52
  • 53
  • 54
  • 55
  • 56
  • 57
  • 58
  • 59
  • 60
  • 61
  • 62
  • 63
  • 64
  • 65
  • 66
  • 67
  • 68
  • 69
  • 70
  • 71
  • 72
  • 73
  • 74
  • 75
  • 76
  • 77
  • 78
  • 79
  • 80
  • 81
  • 82
  • 83
  • 84
  • 85
  • 86
  • 87
  • 88
  • 89
  • 90
  • 91
  • 92
  • 93
  • 94
  • 95
  • 96
  • 97
  • 98
  • 99
  • 100
  • 101
  • 102
  • 103
  • 104
  • 105
  • 106
  • 107
  • 108
  • 109
  • 110
  • 111
  • 112
  • 113
  • 114
  • 115
  • 116
  • 117
  • 118
  • 119
  • 120
  • 121
  • 122
  • 123
  • 124
  • 125
  • 126
  • 127
  • 128
  • 129
  • 130
  • 131
  • 132
  • 133
  • 134
  • 135
  • 136
  • 137
  • 138
  • 139
  • 140
  • 141
  • 142
  • 143
  • 144
  • 145
  • 146
  • 147
  • 148
  • 149
  • 150
  • 151
  • 152
  • 153
  • 154
  • 155
  • 156
  • 157
  • 158
  • 159
  • 160
  • 161
  • 162
  • 163
  • 164
  • 165
  • 166
  • 167
  • 168
  • 169
  • 170
  • 171
  • 172
  • 173
  • 174
  • 175
  • 176
  • 177
  • 178
  • 179
  • 180
  • 181
  • 182
  • 183
  • 184
  • 185
  • 186
  • 187
  • 188
  • 189
  • 190
  • 191
  • 192
  • 193
  • 194
  • 195
  • 196
  • 197
  • 198
  • 199
  • 200
  • 201
  • 202
  • 203
  • 204
  • 205
  • 206
  • 207
  • 208
  • 209
  • 210
  • 211
  • 212
  • 213
  • 214
  • 215
  • 216
  • 217
  • 218
  • 219
  • 220
  • 221
  • 222
  • Next page

Sign up to receive news and updates from MIT Industrial Liaison Program Sign up

  • Read
    • Faculty Features
    • Research
    • News
  • Watch
  • Attend
    • Conferences
    • Webinars
    • Learning Opportunities
  • About
    • Membership
    • Staff
    • For Faculty
  • Connect
    • Faculty/Researchers
    • Program Directors
  • MIT Startup Exchange
  • LinkedIn
  • YouTube
  • Twitter
Home

1 Main Street
12th Floor, E90-1201

Cambridge, MA 02142

Privacy Policy

Accessibility

617-253-2691
ask-ilp@mit.edu

MIT OCR Logo