Dear Allstat member,
n Please note that the dateline for submission for the special session on Machine Learning Applications in Psychiatry is extended until September 17th!
We would welcome submissions form statistician using statistical learning or machine learning methods for the “Special Session on Machine Learning Applications in Psychiatry” at the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA-2018) December 17-20, 2018, Orlando, Florida, USA
www.icmla-conference.org/icmla18<http://www.icmla-conference.org/icmla18>
AIMS AND SCOPE Psychiatric research entered the age of big data with patient databases now available with thousands of clinical, demographical, social, environmental, neuroimaging, genomic, proteonomic and other -omic measures. The analyses of such data is often more challenging than in other medical research areas because i) psychiatrists study traits which are not easily measurable; they need to be measured indirectly e.g. by questionnaires, ii) the definition of a mental disease is often very broad and often includes distinct but unknown subcategories, iii) there is a high proportion of drop-out in many studies and patients often do not adhere to the treatment, iv) treatment interventions often have several interacting and it is often difficult to measure components (complex interventions) and v) data is often not easily available, i.e. much medical and biomedical data is held in unstructured, textual form or is collected with mobile devices Psychiatric research therefore presents special problems for researchers in addition to the standard methodological challenges, such as the number of variables exceeding the number of patients.
Machine learning techniques are increasingly being used to address problems in psychiatric and psychological research, including bioinformatics, neuroimaging, prediction modelling and personalized medicine, causal modelling, epidemiology and many other research areas. We would like to invite researchers from both academia and industry to participate in this workshop to present, discuss, and share the latest findings in the field, and exchange ideas that address real-world problems with real-world solutions, as well as to discuss future research directions.
For more information please see:
http://www.icmla-conference.org/icmla18/Psychiatry.pdf
Dates: Paper Submission Deadline September 7, 2018
Notification of Acceptance October 7, 2018
Camera-Ready Papers & Pre-registration: October 17, 2018
Special Session Chairs Dr. Daniel Stahl, Dep. of Biostatistics and Health Informatics, King’s College London Email: [log in to unmask]<mailto:[log in to unmask]>
Dr. Daniel Stamate, Dep. of Computing, Goldsmiths, University of London Email: [log in to unmask]<mailto:[log in to unmask]>
Kind regards,
Daniel Stahl & Daniel Stamate,
****************************************************************************
Daniel Stahl, PhD
Reader in Biostatistics
Head of Statistical Learning Group
Department of Biostatistics and Health Informatics, S2.05
Institute of Psychiatry, Psychology & Neuroscience, King's College London
De Crespigny Park, Box PO20
London SE5 8AF
Email: [log in to unmask]<mailto:[log in to unmask]>
Tel: 0207 848 0964
https://kclpure.kcl.ac.uk/portal/daniel.r.stahl.html
Statistical Learning Group
www.kcl.ac.uk/statslg<http://www.kcl.ac.uk/statslg>
Department page
http://www.kcl.ac.uk/iop/depts/biostatistics/index.aspx
*** Autumn School Predcition Modelling ***
https://www1.kcl.ac.uk/prospectus/shortcourses/index/name/predictionmodelling/alpha/month/day/header_search/Causal+modelling
Statistical Learning and Prediction Modelling Research Group
https://statlearn-predmodel.wixsite.com/kcl-statlearn/autumn-school-2017
IoPPN Statistics Help Desk
https://www.kcl.ac.uk/ioppn/depts/BiostatisticsHealthInformatics/SAS/index.aspx
From: Stahl, Daniel
Sent: 18 July 2018 10:12
To: [log in to unmask] <[log in to unmask]<mailto:[log in to unmask]>>
Subject: Conference and special session announcement: IEEE International Conference on Machine Learning and Applications (IEEE ICMLA-2018) December 17-20, 2018, Orlando, Florida, USA with “Special Session on Machine Learning Applications in Psychiatry”
Dear allstat members,
We would welcome submissions form statistician using statistical learning or machine learning methods for the “Special Session on Machine Learning Applications in Psychiatry” at the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA-2018) December 17-20, 2018, Orlando, Florida, USA
www.icmla-conference.org/icmla18<http://www.icmla-conference.org/icmla18>
AIMS AND SCOPE Psychiatric research entered the age of big data with patient databases now available with thousands of clinical, demographical, social, environmental, neuroimaging, genomic, proteonomic and other -omic measures. The analyses of such data is often more challenging than in other medical research areas because i) psychiatrists study traits which are not easily measurable; they need to be measured indirectly e.g. by questionnaires, ii) the definition of a mental disease is often very broad and often includes distinct but unknown subcategories, iii) there is a high proportion of drop-out in many studies and patients often do not adhere to the treatment, iv) treatment interventions often have several interacting and it is often difficult to measure components (complex interventions) and v) data is often not easily available, i.e. much medical and biomedical data is held in unstructured, textual form or is collected with mobile devices Psychiatric research therefore presents special problems for researchers in addition to the standard methodological challenges, such as the number of variables exceeding the number of patients.
Machine learning techniques are increasingly being used to address problems in psychiatric and psychological research, including bioinformatics, neuroimaging, prediction modelling and personalized medicine, causal modelling, epidemiology and many other research areas. We would like to invite researchers from both academia and industry to participate in this workshop to present, discuss, and share the latest findings in the field, and exchange ideas that address real-world problems with real-world solutions, as well as to discuss future research directions.
For more information please see:
http://www.icmla-conference.org/icmla18/Psychiatry.pdf
Dates: Paper Submission Deadline September 7, 2018
Notification of Acceptance October 7, 2018
Camera-Ready Papers & Pre-registration: October 17, 2018
Special Session Chairs Dr. Daniel Stahl, Dep. of Biostatistics and Health Informatics, King’s College London Email: [log in to unmask]<mailto:[log in to unmask]>
Dr. Daniel Stamate, Dep. of Computing, Goldsmiths, University of London Email: [log in to unmask]<mailto:[log in to unmask]>
Kind regards,
Daniel Stahl & Daniel Stamate,
****************************************************************************
Daniel Stahl, PhD
Reader in Biostatistics
Head of Statistical Learning Group
Department of Biostatistics and Health Informatics, S2.05
Institute of Psychiatry, Psychology & Neuroscience, King's College London
De Crespigny Park, Box PO20
London SE5 8AF
Email: [log in to unmask]<mailto:[log in to unmask]>
Tel: 0207 848 0964
https://kclpure.kcl.ac.uk/portal/daniel.r.stahl.html
Statistical Learning Group
www.kcl.ac.uk/statslg<http://www.kcl.ac.uk/statslg>
Department page
http://www.kcl.ac.uk/iop/depts/biostatistics/index.aspx
*** Autumn School Predcition Modelling ***
https://www1.kcl.ac.uk/prospectus/shortcourses/index/name/predictionmodelling/alpha/month/day/header_search/Causal+modelling
Statistical Learning and Prediction Modelling Research Group
https://statlearn-predmodel.wixsite.com/kcl-statlearn/autumn-school-2017
IoPPN Statistics Help Desk
https://www.kcl.ac.uk/ioppn/depts/BiostatisticsHealthInformatics/SAS/index.aspx
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