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Data Science and the Study of Alzheimer’s (with Christopher Gaiteri, PhD, Associate Professor of Psychiatry & Behavioral Sciences; Empire Innovation Scholar, SUNY Upstate Medical University)

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Treść dostarczona przez Harris Search Associates. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Harris Search Associates lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

Christopher Gaiteri, Ph.D., is Associate Professor of Psychiatry & Behavioral Sciences and Empire Innovation Scholar at SUNY Upstate Medical University. Dr. Gaiteri earned his undergraduate degree from Washington & Lee University and his doctorate from the University of Pittsburgh. He joined Rush University as assistant professor of neurological sciences and computational neuroscientist after serving as Research Scientist at the Allen Institute for Brain Science and Senior Scientist at Sage Bionetworks.

In today’s podcast, Dr. Gaiteri responds to the following questions:

1. What were the origins to your approach and how does it differ from the more traditional way of framing research about the onset and development of Alzheimer's disease?

2. Statistical techniques such as factor analysis and canonical correlation were used in research to take a large number of measures of variables and allow those statistical techniques to sort out which of those variables covaried and which patterns emerged that could suggest relationships to be looked at more closely.

In your approach using "big data" do you have a particular notion of which variables you select ought to covary? In other words, do you have a "pre-theory" that guides your selection of variables?

3. Alzheimer's is nearly always associated with the aging process, perhaps implicitly arguing that the aging process alone is a causal agent for the onset and progression of the disease. More recently and not without some controversy, some researchers have suggested that aging itself should be considered a disease. From your perspective, does the question of age influence your view on how to go about framing analyses of data bearing on the inception and development of Alzheimer’s?

4. In your career to date, how has the leadership of organizations in which you have worked influenced you and your research? Are there characteristics of persons who hold leadership roles that you single out as especially important to your work?

INNOVATORS is a podcast production of Harris Search Associates.

*The views and opinions shared by the guests on INNOVATORS do not necessarily reflect the views of the interviewee's institution or organization.*
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iconUdostępnij
 
Manage episode 367931387 series 1526434
Treść dostarczona przez Harris Search Associates. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Harris Search Associates lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

Christopher Gaiteri, Ph.D., is Associate Professor of Psychiatry & Behavioral Sciences and Empire Innovation Scholar at SUNY Upstate Medical University. Dr. Gaiteri earned his undergraduate degree from Washington & Lee University and his doctorate from the University of Pittsburgh. He joined Rush University as assistant professor of neurological sciences and computational neuroscientist after serving as Research Scientist at the Allen Institute for Brain Science and Senior Scientist at Sage Bionetworks.

In today’s podcast, Dr. Gaiteri responds to the following questions:

1. What were the origins to your approach and how does it differ from the more traditional way of framing research about the onset and development of Alzheimer's disease?

2. Statistical techniques such as factor analysis and canonical correlation were used in research to take a large number of measures of variables and allow those statistical techniques to sort out which of those variables covaried and which patterns emerged that could suggest relationships to be looked at more closely.

In your approach using "big data" do you have a particular notion of which variables you select ought to covary? In other words, do you have a "pre-theory" that guides your selection of variables?

3. Alzheimer's is nearly always associated with the aging process, perhaps implicitly arguing that the aging process alone is a causal agent for the onset and progression of the disease. More recently and not without some controversy, some researchers have suggested that aging itself should be considered a disease. From your perspective, does the question of age influence your view on how to go about framing analyses of data bearing on the inception and development of Alzheimer’s?

4. In your career to date, how has the leadership of organizations in which you have worked influenced you and your research? Are there characteristics of persons who hold leadership roles that you single out as especially important to your work?

INNOVATORS is a podcast production of Harris Search Associates.

*The views and opinions shared by the guests on INNOVATORS do not necessarily reflect the views of the interviewee's institution or organization.*
  continue reading

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