Webinar on How big data and AI improve perioperative management and outcome

schedule

Tuesday, March 22, 1:00pm - 2:00pm (EDT)

south_america expand_more Time shown in-05:00 America, New York
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24h

  • (GMT-11:00)Pacific, Midway
  • (GMT-11:00)Pacific, Niue
  • (GMT-11:00)Pacific, Pago Pago
  • (GMT-10:00)America, Adak
  • (GMT-10:00)Pacific, Honolulu
  • (GMT-10:00)Pacific, Rarotonga
  • (GMT-10:00)Pacific, Tahiti
  • (GMT-09:30)Pacific, Marquesas
  • (GMT-09:00)America, Anchorage
  • (GMT-09:00)America, Juneau
  • (GMT-09:00)America, Metlakatla
  • (GMT-09:00)America, Nome
  • (GMT-09:00)America, Sitka
  • (GMT-09:00)America, Yakutat
  • (GMT-09:00)Pacific, Gambier
  • (GMT-08:00)America, Los Angeles
  • (GMT-08:00)America, Tijuana
  • (GMT-08:00)America, Vancouver
  • (GMT-08:00)Pacific, Pitcairn
  • (GMT-07:00)America, Boise
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  • (GMT-07:00)America, Creston
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  • (GMT-07:00)America, Dawson Creek
  • (GMT-07:00)America, Denver
  • (GMT-07:00)America, Edmonton
  • (GMT-07:00)America, Fort Nelson
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  • (GMT-07:00)America, Ojinaga
  • (GMT-07:00)America, Phoenix
  • (GMT-07:00)America, Whitehorse
  • (GMT-07:00)America, Yellowknife
  • (GMT-06:00)America, Bahia Banderas
  • (GMT-06:00)America, Belize
  • (GMT-06:00)America, Chicago
  • (GMT-06:00)America, Costa Rica
  • (GMT-06:00)America, El Salvador
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  • (GMT-06:00)America, Indiana, Knox
  • (GMT-06:00)America, Indiana, Tell City
  • (GMT-06:00)America, Managua
  • (GMT-06:00)America, Matamoros
  • (GMT-06:00)America, Menominee
  • (GMT-06:00)America, Merida
  • (GMT-06:00)America, Mexico City
  • (GMT-06:00)America, Monterrey
  • (GMT-06:00)America, North Dakota, Beulah
  • (GMT-06:00)America, North Dakota, Center
  • (GMT-06:00)America, North Dakota, New Salem
  • (GMT-06:00)America, Rainy River
  • (GMT-06:00)America, Rankin Inlet
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  • (GMT-06:00)America, Winnipeg
  • (GMT-06:00)Pacific, Galapagos
  • (GMT-05:00)America, Atikokan
  • (GMT-05:00)America, Bogota
  • (GMT-05:00)America, Cancun
  • (GMT-05:00)America, Cayman
  • (GMT-05:00)America, Detroit
  • (GMT-05:00)America, Eirunepe
  • (GMT-05:00)America, Grand Turk
  • (GMT-05:00)America, Guayaquil
  • (GMT-05:00)America, Havana
  • (GMT-05:00)America, Indiana, Indianapolis
  • (GMT-05:00)America, Indiana, Marengo
  • (GMT-05:00)America, Indiana, Petersburg
  • (GMT-05:00)America, Indiana, Vevay
  • (GMT-05:00)America, Indiana, Vincennes
  • (GMT-05:00)America, Indiana, Winamac
  • (GMT-05:00)America, Iqaluit
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  • (GMT-05:00)America, Kentucky, Louisville
  • (GMT-05:00)America, Kentucky, Monticello
  • (GMT-05:00)America, Lima
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  • (GMT-05:00)America, New York
  • (GMT-05:00)America, Nipigon
  • (GMT-05:00)America, Panama
  • (GMT-05:00)America, Pangnirtung
  • (GMT-05:00)America, Port-au-Prince
  • (GMT-05:00)America, Rio Branco
  • (GMT-05:00)America, Thunder Bay
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  • (GMT-05:00)Pacific, Easter
  • (GMT-04:00)America, Anguilla
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  • (GMT-04:00)America, Barbados
  • (GMT-04:00)America, Blanc-Sablon
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  • (GMT-04:00)America, Port of Spain
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  • (GMT-04:00)America, St Vincent
  • (GMT-04:00)America, Thule
  • (GMT-04:00)America, Tortola
  • (GMT-04:00)Atlantic, Bermuda
  • (GMT-03:30)America, St Johns
  • (GMT-03:00)America, Araguaina
  • (GMT-03:00)America, Argentina, Buenos Aires
  • (GMT-03:00)America, Argentina, Catamarca
  • (GMT-03:00)America, Argentina, Cordoba
  • (GMT-03:00)America, Argentina, Jujuy
  • (GMT-03:00)America, Argentina, La Rioja
  • (GMT-03:00)America, Argentina, Mendoza
  • (GMT-03:00)America, Argentina, Rio Gallegos
  • (GMT-03:00)America, Argentina, Salta
  • (GMT-03:00)America, Argentina, San Juan
  • (GMT-03:00)America, Argentina, San Luis
  • (GMT-03:00)America, Argentina, Tucuman
  • (GMT-03:00)America, Argentina, Ushuaia
  • (GMT-03:00)America, Asuncion
  • (GMT-03:00)America, Bahia
  • (GMT-03:00)America, Belem
  • (GMT-03:00)America, Cayenne
  • (GMT-03:00)America, Fortaleza
  • (GMT-03:00)America, Maceio
  • (GMT-03:00)America, Miquelon
  • (GMT-03:00)America, Montevideo
  • (GMT-03:00)America, Nuuk
  • (GMT-03:00)America, Paramaribo
  • (GMT-03:00)America, Punta Arenas
  • (GMT-03:00)America, Recife
  • (GMT-03:00)America, Santarem
  • (GMT-03:00)America, Santiago
  • (GMT-03:00)America, Sao Paulo
  • (GMT-03:00)Antarctica, Palmer
  • (GMT-03:00)Antarctica, Rothera
  • (GMT-03:00)Atlantic, Stanley
  • (GMT-02:00)America, Noronha
  • (GMT-02:00)Atlantic, South Georgia
  • (GMT-01:00)America, Scoresbysund
  • (GMT-01:00)Atlantic, Azores
  • (GMT-01:00)Atlantic, Cape Verde
  • (GMT+00:00)Africa, Abidjan
  • (GMT+00:00)Africa, Accra
  • (GMT+00:00)Africa, Bamako
  • (GMT+00:00)Africa, Banjul
  • (GMT+00:00)Africa, Bissau
  • (GMT+00:00)Africa, Conakry
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  • (GMT+00:00)Africa, Ouagadougou
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  • (GMT+00:00)America, Danmarkshavn
  • (GMT+00:00)Antarctica, Troll
  • (GMT+00:00)Atlantic, Canary
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  • (GMT+00:00)Atlantic, Madeira
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  • (GMT+00:00)Europe, Isle of Man
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  • (GMT+00:00)Europe, Lisbon
  • (GMT+00:00)Europe, London
  • (GMT+00:00)UTC
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  • (GMT+01:00)Africa, Ceuta
  • (GMT+01:00)Africa, Douala
  • (GMT+01:00)Africa, El Aaiun
  • (GMT+01:00)Africa, Kinshasa
  • (GMT+01:00)Africa, Lagos
  • (GMT+01:00)Africa, Libreville
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  • (GMT+01:00)Africa, Porto-Novo
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  • (GMT+01:00)Arctic, Longyearbyen
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  • (GMT+01:00)Europe, Luxembourg
  • (GMT+01:00)Europe, Madrid
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  • (GMT+01:00)Europe, Monaco
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  • (GMT+01:00)Europe, Stockholm
  • (GMT+01:00)Europe, Tirane
  • (GMT+01:00)Europe, Vaduz
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  • (GMT+01:00)Europe, Vienna
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  • (GMT+02:00)Africa, Blantyre
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  • (GMT+02:00)Africa, Gaborone
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  • (GMT+02:00)Africa, Khartoum
  • (GMT+02:00)Africa, Kigali
  • (GMT+02:00)Africa, Lubumbashi
  • (GMT+02:00)Africa, Lusaka
  • (GMT+02:00)Africa, Maputo
  • (GMT+02:00)Africa, Maseru
  • (GMT+02:00)Africa, Mbabane
  • (GMT+02:00)Africa, Tripoli
  • (GMT+02:00)Africa, Windhoek
  • (GMT+02:00)Asia, Amman
  • (GMT+02:00)Asia, Beirut
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  • (GMT+03:00)Europe, Istanbul
  • (GMT+03:00)Europe, Kirov
  • (GMT+03:00)Europe, Minsk
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  • (GMT+04:00)Europe, Astrakhan
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  • (GMT+06:00)Indian, Chagos
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    Scientific Faculty

    Host

    Prof Teodora Nicolescu

    President of the European Society of Computing and Technology in Anesthesiology and Intensive Care

    Oklahoma University Health Sciences Center



    Speakers

    Prof. Elena Giovanna Bignami

    Director of the School of Specialization in Anesthesia Intensive Care and Pain

    President of the Nursing Course, Department of Medicine and Surgery

    University Hospital of Parma



    Dr. Matthieu Komorowski

    Consultant in Intensive Care

    Charing Cross Hospital – Imperial College London



    Target Audience

    Anesthesiologists, residents, nurse anesthetists

    Key points

    The webinar will address :

    Utilization of high quality data collection as predictive models for perioperative patient management

    Efficient and discrete data sampling for perioperative patient course assessment

    Extrapolate the current knowledge for future data modelling and more expansive AI use(Watson)





    About this webinar

    The webinar will inform the audience of the newest predictive models for perioperative patient management and how to effectively use data collection to review and improve both quality of care and patient safety.



    Content

    Artificial intelligence has been an adjuvant for a multitude of scientific fields, anesthesiology being one of those. The aspects AI applications that are most useful are:

    Depth of anesthesia monitoring and control of anesthesia

    Event and risk prediction

    Ultrasound guidance

    Pain management

    Operating room logistics

    Artificial intelligence has the potential to not only impact the perioperative management but the intensive care unit as well.

    The webinar will describe:

    The importance of appropriate of data mining and collection, using such data for predictive modelling that aids not only in the perioperative patient management, pain control or ICU course but also in ultimately identifying risk during the preoperative patients’ evaluation.

    As AI is progressing to supercomputer use, anesthesiologists will have to adapt to a new way of practice and be aware of both the advantages and limitations of AI use.



    Learning Objectives

    This webinar will enable anaesthesiologists and intensivists to:

    Identify which data collection most effectively can aid in perioperative patient management

    Describe the predictive modelling , its utilization and its impact on quality of care

    Apply the principles of predictive modelling to daily patient care management



    Practical skills to be acquired after attending to this Webinar

    The user is able to:

    Create predictive models which are effective aids

    Demonstrate the impact of AI use in improving quality of care

    Obtain new skills related to data mining and collection



    Affective skills acquired after attending to this Webinar

    The participants are aware of:

    Importance of the specifications and use of data collection

    Advocating for patient safety of the use of predictive models

    Need to reflect on the future shaping of the field of anesthesiology by new supercomputers AI such as Watson

    The participant will be able to:

    Evaluate the impact of predictive models on patient management

    Specify challenging aspects or limitations of models

    Test the resilience of predictive models in long term utilization



    Needs analysis

    Anesthesiology as a field is well positioned to potentially benefit from advances in artificial intelligence as it touches on multiple elements of clinical care, including perioperative and intensive care, pain management, and drug delivery and discovery. The webinar is a scoping review of the literature at the intersection of artificial intelligence and anesthesia with the goal of identifying techniques from the field of artificial intelligence that are being used in anesthesia research and their applications to the clinical practice of anesthesiology.



    Technical Settings

    This webinar is available on PC, Tablet and Smartphone.

    For the best viewing experience, a high-speed internet connection is required.



    This Webinar is supported an unrestricted educational grant by GE Healthcare.

    Add to Calendar 2022/03/22 18:00:00 2022/03/22 19:00:00 Europe/Brussels Webinar on How big data and AI improve perioperative management and outcome Scientific Faculty

    Host

    Prof Teodora Nicolescu

    President of the European Society of Computing and Technology in Anesthesiology and Intensive Care

    Oklahoma University Health Sciences Center



    Speakers

    Prof. Elena Giovanna Bignami

    Director of the School of Specialization in Anesthesia Intensive Care and Pain

    President of the Nursing Course, Department of Medicine and Surgery

    University Hospital of Parma



    Dr. Matthieu Komorowski

    Consultant in Intensive Care

    Charing Cross Hospital – Imperial College London



    Target Audience

    Anesthesiologists, residents, nurse anesthetists

    Key points

    The webinar will address :

    Utilization of high quality data collection as predictive models for perioperative patient management

    Efficient and discrete data sampling for perioperative patient course assessment

    Extrapolate the current knowledge for future data modelling and more expansive AI use(Watson)





    About this webinar

    The webinar will inform the audience of the newest predictive models for perioperative patient management and how to effectively use data collection to review and improve both quality of care and patient safety.



    Content

    Artificial intelligence has been an adjuvant for a multitude of scientific fields, anesthesiology being one of those. The aspects AI applications that are most useful are:

    Depth of anesthesia monitoring and control of anesthesia

    Event and risk prediction

    Ultrasound guidance

    Pain management

    Operating room logistics

    Artificial intelligence has the potential to not only impact the perioperative management but the intensive care unit as well.

    The webinar will describe:

    The importance of appropriate of data mining and collection, using such data for predictive modelling that aids not only in the perioperative patient management, pain control or ICU course but also in ultimately identifying risk during the preoperative patients’ evaluation.

    As AI is progressing to supercomputer use, anesthesiologists will have to adapt to a new way of practice and be aware of both the advantages and limitations of AI use.



    Learning Objectives

    This webinar will enable anaesthesiologists and intensivists to:

    Identify which data collection most effectively can aid in perioperative patient management

    Describe the predictive modelling , its utilization and its impact on quality of care

    Apply the principles of predictive modelling to daily patient care management



    Practical skills to be acquired after attending to this Webinar

    The user is able to:

    Create predictive models which are effective aids

    Demonstrate the impact of AI use in improving quality of care

    Obtain new skills related to data mining and collection



    Affective skills acquired after attending to this Webinar

    The participants are aware of:

    Importance of the specifications and use of data collection

    Advocating for patient safety of the use of predictive models

    Need to reflect on the future shaping of the field of anesthesiology by new supercomputers AI such as Watson

    The participant will be able to:

    Evaluate the impact of predictive models on patient management

    Specify challenging aspects or limitations of models

    Test the resilience of predictive models in long term utilization



    Needs analysis

    Anesthesiology as a field is well positioned to potentially benefit from advances in artificial intelligence as it touches on multiple elements of clinical care, including perioperative and intensive care, pain management, and drug delivery and discovery. The webinar is a scoping review of the literature at the intersection of artificial intelligence and anesthesia with the goal of identifying techniques from the field of artificial intelligence that are being used in anesthesia research and their applications to the clinical practice of anesthesiology.



    Technical Settings

    This webinar is available on PC, Tablet and Smartphone.

    For the best viewing experience, a high-speed internet connection is required.



    This Webinar is supported an unrestricted educational grant by GE Healthcare.
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    ESAIC, esa.galleries@gmail.com