Two Data mining application seminars

Two announcements about data mining applications. Either could be a model for a project, especially if the authors would share some data. The first one is clearly interested in hiring. I can’t predict what fraction of his talk will be about pure algorithms, and what fraction will be relevant to our course, but there will be some of each.


1. Tech Talk: Machine Learning and AI Monday night

Monday, April 16, 2018 6:00 – 7:00 PM.
Jacobs Hall – Qualcomm Conference Center
Speaker: Abhijeet Gulati M.S. (UCSD) Director, AI & Product Delivery
Learn how Mitchell International is using Machine Learning & AI to fundamentally disrupt automotive claims management and collision repair industry. Abhijeet Gulati, will discuss Mitchell’s path to Artificial Intelligence and its game changing future.
Machine Learning as a service [MLaaS]
  • Claims workflow lifecycle
  • First notice of loss and damage triage
  • Guided Estimating


2. “Hazed and Confused: Air Pollution, Dementia, and Financial Decision Making”  Seminar Wednesday 

Nicolai Kuminoff
Arizona State University
Wednesday, April 18, 12:10 pm – 1:30 pm
Never mind – this one is at Berkeley! But the topic is relevant. 

Abstract: We study whether long-term exposure to air pollution impairs cognition among the US Medicare population. We link fifteen years of administrative records for 7.4 million adults age 65 and older to the Environmental Protection Agency’s air-quality monitoring network to track the evolution of individuals’ health, onset of Alzheimer’s disease and related forms of dementia, financial decisions, and cumulative exposure to fine-particulate air pollution (PM2.5) based on their precise residential locations. We see evidence of Tiebout’s mechanism at work: movers tend to move to less polluted neighborhoods but, among movers, those who are older and those with dementia tend to move to more polluted neighborhoods. We address residential sorting and measurement error in assigning pollution to people by utilizing quasi-random variation in PM2.5 exposures stemming from the EPA’s initial (2005) designation of nonattainment counties for PM2.5. We find robust evidence that a 1 microgram per cubic meter (μg/m3) increase in decadal exposure to PM2.5 (8.5% of the mean) increases the probability of an dementia diagnosis by the end of the decade by 0.5 to 1.2 percentage points (4% to 6%). Our estimates are slightly larger at exposure levels below the EPA’s current regulatory threshold.  We also find that higher cumulative exposures to PM2.5 impair financial decision making among those not diagnosed with dementia, where the magnitudes of the effects are 3% to 6% of the negative effect of dementia on decision making. Finally, we find no evidence that exposure to PM2.5 affects the diagnosis rates for morbidities thought to be unrelated to air-pollution and no evidence that pollutants other than PM2.5 impair cognition, providing evidence against confounding.

Author: Roger Bohn

Professor of Technology Management, UC San Diego. Visiting Stanford Medical School Twitter =Roger.Bohn

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