Fwd: MACHINE LEARNING in MEDICINE - VIRTUAL SEMINAR - FEBRUARY 9, 2022 - 3PM (EST) ---ZOOM INFO BELOW

Fri Feb 4 12:14:38 EST 2022

This could be of interest to many of us.

Artur

---------- Forwarded message ---------
From: Christy Melucci <cmelucci at andrew.cmu.edu>
Date: Fri, Feb 4, 2022, 11:57 AM
Subject: RE: MACHINE LEARNING in MEDICINE - VIRTUAL SEMINAR - FEBRUARY 9,
2022 - 3PM (EST) ---ZOOM INFO BELOW
To: ml-seminar at cs.cmu.edu <ml-seminar at cs.cmu.edu>,
ml-core-faculty at cs.cmu.edu <ml-core-faculty at cs.cmu.edu>
Cc: Visweswaran, Shyam <shv3 at pitt.edu>, Bartolotta, Genine M <
bartgm at pitt.edu>, Batmanghelich, Kayhan <kayhan at pitt.edu>

*From:* Bartolotta, Genine M <bartgm at pitt.edu>
*Sent:* Friday, February 4, 2022 11:50 AM
*Cc:* Batmanghelich, Kayhan <kayhan at pitt.edu>; Visweswaran, Shyam <
shv3 at pitt.edu>
*Subject:* MACHINE LEARNING in MEDICINE - VIRTUAL SEMINAR - FEBRUARY 9,
2022 - 3PM (EST) ---ZOOM INFO BELOW

*Machine Learning in Medicine (MLxMed)*

*A Virtual Seminar Series in Pittsburgh*

*Hosted by the Department of Biomedical Informatics*

*Wednesday, February 9, 2022*

*3:00 PM – 4:00 PM Eastern Time University of Pittsburgh, UPMC, CMU, and
University of Toronto*

*Temporal data analytics for clinical decision support*

*Zoom **https://pitt.zoom.us/j/96664947180*
<https://pitt.zoom.us/j/96664947180>

(*Details are listed at the end*)

*Lucia Sacchi, PhD*

Associate Professor, Department of Electrical, Computer and Biomedical
Engineering, University of Pavia, Italy

*Abstract: *The data collected during the medical history of a patient are
often longitudinal in nature. Moreover, they can come from different
sources (hospital, home monitoring), and be collected with different
purposes (clinical or billing purposes), thus resulting in heterogeneous
formats and granularities. The definition of analytics techniques able to
deal with these unique characteristics of the data is important for
enhancing decision support with features that take into account the
temporal evolution of the disease and the involved processes of care. This
talk will explore temporal analytics techniques applied to the analysis of
heterogeneous data for clinical decision support. In particular, we will
consider electronic temporal phenotyping as the identification of
clinically meaningful event sequences from data that have been collected
over time, and its application to diabetes, cancer, and COVID-19.

*About MLxMed Seminar Series*

*(**http://ml-in-medicine.org/*
<https://nam05.safelinks.protection.outlook.com/?url=http%3A%2F%2Fml-in-medicine.org%2F&data=02%7C01%7Ccafeo%40pitt.edu%7Cfd9284768d884c01352b08d816ea4fa8%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C637284542905912546&sdata=6NKlakpjZ8taWQlU7RklCdS%2F7tDHw6SIhKAfiZYtr8M%3D&reserved=0>
*)*

Medicine is complex and data-driven while discovery and decision making are
increasingly enabled by machine learning. Machine learning has the
potential to support, enable and improve medical discovery and clinical
decision making in areas such as medical imaging, cancer diagnostics,
precision medicine, clinical trials, and electronic health records. This
seminar series focuses on new algorithms, real-world deployment, and future
trends in machine learning in medicine. It will feature prominent
investigators who are developing and applying machine learning to
biomedical discovery and in clinical decision support. For more information
see MLxMed website.

*Zoom Information*

*When: February 9, 2022 - 03:00 PM Eastern Time (US and Canada)*

*Please click the link below to join the webinar:*

*https://pitt.zoom.us/j/96664947180* <https://pitt.zoom.us/j/96664947180>

Or One tap mobile :

    US: *+12678310333,,96664947180#  or 8778535247,,96664947180# *(Toll
Free)

Or Telephone:

    Dial(for higher quality, dial a number based on your current location):

*        US: +1 267 831 0333  or 877 853 5247 (Toll Free)*

*Webinar ID: 966 6494 7180*

    International numbers available: *https://pitt.zoom.us/u/adTD7fZxpk*
<https://pitt.zoom.us/u/adTD7fZxpk>

Or an H.323/SIP room system:

    H.323:

    162.255.37.11 (US West)

    162.255.36.11 (US East)

    115.114.131.7 (India Mumbai)

    115.114.115.7 (India Hyderabad)

    213.19.144.110 (Amsterdam Netherlands)

    213.244.140.110 (Germany)

    103.122.166.55 (Australia Sydney)

    103.122.167.55 (Australia Melbourne)

    149.137.40.110 (Singapore)

    64.211.144.160 (Brazil)

    149.137.68.253 (Mexico)

    69.174.57.160 (Canada Toronto)

    65.39.152.160 (Canada Vancouver)

    207.226.132.110 (Japan Tokyo)

    149.137.24.110 (Japan Osaka)

    *Meeting ID: 966 6494 7180*

*    SIP: **96664947180 at zoomcrc.com* <96664947180 at zoomcrc.com>

*Genine M. Bartolotta*

*Department of Biomedical Informatics*

*University of Pittsburgh, School of Medicine*

The Offices at Baum, Fourth Floor

5607 Baum Boulevard

Pittsburgh, PA  15206-3701

Phone: (412) 624-5100

Cell Phone: (412) 877-4872

FAX: (412) 648-9118

E-mail: *bartgm at pitt.edu <bartgm at pitt.edu> (preferred)*

bartolottagm at upmc.edu

*This e-mail may contain confidential information of the sending*

*organization. Any unauthorized or improper disclosure, copying,*

*distribution, or use of the contents of this e-mail and attached*

*document(s) is prohibited.  The information contained in this*

*e-mail and attached document(s)is intended only for the*

*personal and confidential use of the recipient(s) named*

*in original e-mail and attached document(s).*
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