[Corpora-List] CFP: 3rd International Workshop on Knowledge Discovery in Healthcare Data (@ IJCAI-ECAI 2018)

Sadid Hasan sadidhasan at gmail.com
Fri Mar 9 18:16:55 CET 2018

*The 3rd International Workshop on Knowledge Discovery in Healthcare Data (KDH) 2018*

Website: https://sites.google.com/view/kdhd-2018/home

The Knowledge Discovery in Healthcare Data (KDH) workshop series was established in 2016 to present AI research efforts to solve pressing problems in healthcare. The workshop series aims to bring together clinical and AI researchers to foster collaborative discussions. This year, the workshop will be co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018, https://www.ijcai-18.org/) in Stockholm, Sweden and the focus will be on learning healthcare systems. For the first time, this workshop will feature a challenge: The Machine Learning Blood Glucose Level Prediction Challenge ( https://sites.google.com/view/kdhd-2018/bglp-challenge).

*Call for Papers* ---------------------------

There are many healthcare datasets consisting of both structured and unstructured information, which provide a challenge for artificial intelligence and machine learning researchers seeking to extract knowledge from data. Existing healthcare datasets include electronic medical records, large collections of complex physiological information, medical imaging data, genomics, as well as other socio-economic and behavioral data. In order to perform data-driven analysis or build causal and inferential models using these datasets, challenges such as integrating multiple data types, dealing with missing data and handling irregularly sampled data, need to be addressed. While these challenges need to be considered by researchers working with healthcare data, a larger problem involves how to best ensure the hypotheses posed and types of knowledge discoveries sought are relevant to the healthcare community. Clinical perspectives from medical professionals are required to assure that advancements in healthcare data analysis results in positive impact to eventual point-of-care and outcome-based systems.

This workshop will build on previously held successful Knowledge Discovery in Healthcare Data workshops and will align with this year’s theme of Evolution of the Contours of AI by welcoming contributions providing insight on the extent to which AI techniques have successfully penetrated the healthcare field, interaction among AI techniques to achieve a successful learning healthcare system and the distinction between AI and non-AI models needed in modern healthcare environments. The workshop will focus on discussing issues in data extraction and assembly, knowledge discovery and personalized decision support to care providers and self-care aiding tools to patients.


Contributions are welcome in areas including, but not limited to, the following:

- Data extraction, organization & assembly

- Knowledge-driven and data-driven approaches for information

retrieval and data mining

- Multilevel data integration in healthcare, e.g. behavioral data,

diagnoses, vitals, radiology imaging, Doctor's notes, phenotype, and

different omics data, including multi-agent approaches.

- Integration and use of medical ontologies.

- Knowledge abstraction, classification, and summarization from

literature or electronic health records

- Biomedical data generation and curation

- Knowledge discovery & analytics

- Handling uncertainty in large healthcare datasets: dealing with

missing values and non-uniformly sampled data

- Detecting and extracting hidden information from healthcare data

- The rise of Artificial neural network models or deep learning

approaches for healthcare data analytics

- Extracting causal relationships from healthcare data

- Predictive and prescriptive analyses of healthcare data

- Applications of probabilistic analysis in medicine

- Development of novel diagnostic and prognostic tests utilizing

quantitative data analysis

- Mathematical model development in biology and medicine, modeling of

disease interaction and progression

- Novel visualization techniques

- Active, transfer and reinforcement learning in healthcare

- Physiological data analysis

- Personalization and decision support

- Mobile agents in hospital environment

- Patient Empowerment through personalized patient-centered systems

- Autonomous and remote care delivery

- Medical Decision Support Systems, including Recommender Systems

- Automation of clinical trials, including implementation of adaptive

and platform trial designs.

- Applications of IoT (wearables, sensors, etc.) in healthcare

- Clinical decision support systems

- Blood glucose level prediction

- System description papers detailing results of the BGLP Challenge

- Scientific papers presenting new research in machine learning for

blood glucose level prediction

*Submission & Format*

Submissions can be made as:

1. *Long papers (7 pages + 1 page references):* Long papers should

present original research work and be no longer than eight pages in total:

seven pages for the main text of the paper (including all figures but

excluding references), and one additional page for references. Papers

reporting on original research in blood glucose level prediction, *but

not BGLP Challenge system description papers* should be formatted as

long papers and submitted by the deadline for all workshop papers.

2. *Short papers (4 pages + 1 page references):* Short papers may report

on works in progress, descriptions of available datasets, as well as data

collection efforts. Position papers regarding potential research challenges

are also welcomed. Short paper submissions should be no longer than five

pages in total: four pages for the main text of the paper (including all

figures but excluding references), and one additional page for references.

BGLP Challenge system description papers should be formatted as short

papers; however, these papers have their own submission deadline.

Both long and short papers must be formatted according to IJCAI guidelines <http://www.google.com/url?q=http%3A%2F%2Fwww.ijcai.org%2Fauthors_kit&sa=D&sntz=1&usg=AFQjCNEYQ1Qx5vaqfJmZXf21mZV1dhKr2A> and submitted electronically through EasyChair: https://easychair.org/conferences/?conf=kdh2018 <https://www.google.com/url?q=https%3A%2F%2Feasychair.org%2Fconferences%2F%3Fconf%3Dkdh2018&sa=D&sntz=1&usg=AFQjCNG-RexYJgbJUNciFES_bimXrRvb0w> .


*Proceedings:* The papers accepted for KDH 2018 will be published in the CEUR-WS.org international proceedings volume <http://www.google.com/url?q=http%3A%2F%2Fceur-ws.org%2F&sa=D&sntz=1&usg=AFQjCNEBm1QvnYY6Vm7SnigPfVyTcXDYgQ>. This proceedings volume will be published electronically and indexed by Google Scholar and DBLP.

*Organizing Committee* -------------------------------

Kerstin Bach, Norwegian University of Science and Technology, Norway

Razvan Bunescu, Ohio University, USA

Oladimeji Farri, Philips Research, USA

Aili Guo, Ohio University, USA

Sadid Hasan, Philips Research, USA

Zina Ibrahim, King's College London, UK

Cindy Marling, Ohio University, USA

Jesse Raffa, Massachusetts Institute of Technology, USA

Jonathan Rubin, Philips Research, USA

Honghan Wu, University of Edinburgh, UK

*Program Committee* (to be updated) ----------------------------- Rui Abreu, University of Lisbon, Portugal

Isabelle Bichindaritz, State University of New York at Oswego, USA

Ali Cinar, Illinois Institute of Technology, USA

Josť Manuel Colmenar, King Juan Carlos University, Spain

Sergio Consoli, Philips Research, Netherlands

Alexandra Constantin, Bigfoot Biomedical, USA

Vivek Datla, Philips Research, USA

Spiros Denaxas, University College London, UK

Andrea Facchinetti, University of Padua, Italy

Pau Herrero, Imperial College London, UK

Jose Ignacio Hidalgo, Complutense University of Madrid, Spain

Yuan Ling, Philips Research, USA

Bo Liu, Auburn University, USA

Stewart Massie, Robert Gordon University, UK

Anna Rumshisky, University of Massachusetts Lowell, USA

Sadiq Sani, Robert Gordon University, UK

Alexander Schliep, Gothenburg University, Sweden

Rushdi Shams, OneClass, Canada

Josep Vehi, University of Girona, Spain

*Important Dates* ------------------------

*Technical Papers*

- Paper Submission Deadline: April 23, 2018

- Notification of Acceptance: May 14, 2018

- Camera-Ready Deadline: June 8, 2018

*BGLP Challenge*

- Training and Development Data Release: Feb 21, 2018

- Test Data Release: May 21, 2018

- Results Submission Deadline: June 7, 2018

- System Description Paper Submission Deadline: June 21, 2018

- Notification Date: June 28, 2018

- Camera-Ready Deadline: July 7, 2018

Please feel free to contact organizing committee members should you have any questions/concerns.

Thank you. *Sadid Hasan, PhD.* Senior Scientist, Artificial Intelligence Lab Philips Research North America Web: www.sadidhasan.com -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 30428 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20180309/d22ebd80/attachment.txt>

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