news etc

_bibliography/measuresandmetrics.bib

@@ -0,0 +1,100 @@
+---
+---
+
+%special fields include abbr, award, pdf, html, abstract, slides, video, selected, projectoutput
+
+@InProceedings{report-template,
+      title       = {TODO},
+      author      = {Last, First and Last, First ...},
+      institution = {TODO},
+      address     = {CITY, STATE, COUNTRY},
+      number      = {TODO},
+      year        = {1900},
+      month       = {},
+      abbr={TODO},
+      html={TODO},
+      pdf={TODO},
+      abstract={TODO},
+      code={TODO}
+    }
+
+%daisam reference
+@InProceedings{daisamref,
+      title       = {Data and artificial intelligence assessment methods (DAISAM) reference},
+      author      = {Oala, Luis and Balachandran, Pradeep and Cabitza, Federico and Calderon Ramirez, Saul and Chiavegatto Filho, Alexandre and Eitel, Fabian and Extermann, Jérôme and Fehr, Jana and Ghozzi, Stephane and Gilli, Luca and Jaramillo-Gutierrez, Giovanna and Kester, Quist-Aphetsi and Kurapati, Shalini and Konigorski, Stefan and Krois, Joachim and Lippert, Christoph and Martin, Jörg and Merola, Alberto and Murchison, Andrew and Niehaus, Sebastian and Ritter, Kerstin and Samek, Wojciech and Sanguinetti, Bruno and Schwerk, Anne and Srinivasan, Vignesh},
+      booktitle = 	 {Proceedings of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) - Meeting I},
+      year        = {2020},
+      month       = {May},
+      abbr={ITU/WHO},
+      html={https://extranet.itu.int/sites/itu-t/focusgroups/ai4h/_layouts/15/WopiFrame.aspx?sourcedoc=%7B32FEDFE7-FAF9-476E-81EC-AD06FB956528%7D&file=FGAI4H-I-035.docx&action=default&CT=1614746953719&OR=DocLibClassicUI},
+      pdf={standards/FGAI4H-I-035.pdf},
+      projectoutput = {true},
+      abstract={This document, Data and artificial intelligence assessment methods (DAISAM) reference, is the reference collection of WG-DAISAM for assessment methods of data and artificial intelligence quality evaluation. This document also constitutes subsection 7.3 of the FG-AI4H deliverable 7.}
+    }
+
+
+%regulatory doc
+@InProceedings{regGMLP,
+      title       = {Good practices for health applications of machine learning: Considerations for manufacturers and regulators},
+      author      = {Christian Johner and Pradeep Balachandran and Luis Oala and Aaron .Y. Lee and Alixandro Werneck Leite and Andrew Murchison and Anle Lin and Christoph Molnar and Juliet Rumball-Smith and Pat Baird and Peter. G. Goldschmidt and Pierre Quartarolo and Shan Xu and Sven Piechottka and Zack Hornberger},
+      booktitle = 	 {Proceedings of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) - Meeting K},
+      year        = {2021},
+      month       = {ITU/WHO},
+      abbr={ITU/WHO},
+      html={https://extranet.itu.int/sites/itu-t/focusgroups/ai4h/_layouts/15/WopiFrame.aspx?sourcedoc=%7B828882B2-4941-452C-8A61-F4DDE5802C2A%7D&file=FGAI4H-K-039.docx&action=default&CT=1614782367878&OR=DocLibClassicUI},
+      pdf={standards/FGAI4H-K-039.pdf},
+      abstract={This document contains the latest draft of the FG-AI4H deliverable DEL02.2 "Good practices for health applications of machine learning: Considerations for manufacturers and regulators". This deliverable defines a set of guidelines intended to serve the AI solution developers/manufacturers on how to do conduct a comprehensive requirements analysis and to streamline the conformity assessment procedures to ensure regulatory compliance for the AI based Medical Devices (AI/ML-MD).},
+      selected = {true},
+    }
+
+%training and test data specification
+@InProceedings{AuditReportTemplate,
+      title       = {Data and artificial intelligence assessment methods (DAISAM) Audit Reporting Template},
+      author      = {Boris Verks and Luis Oala},
+      institution = {International Telecommunications Union},
+      address     = {Geneva, Switzerland},
+      number      = {FGAI4H-J-048},
+      booktitle = 	 {Proceedings of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) - Meeting J},
+      year        = {2020},
+      month       = {},
+      abbr={ITU/WHO},
+      html={https://extranet.itu.int/sites/itu-t/focusgroups/ai4h/_layouts/15/WopiFrame.aspx?sourcedoc=%7B3DAE32A1-24FF-4F4D-A735-F378056BA6CF%7D&file=FGAI4H-J-048.docx&action=default&CT=1614791061573&OR=DocLibClassicUI},
+      pdf={standards/FGAI4H-J-048.pdf},
+      abstract={Standardized templates to report results for the assessment processes developed by WG-DAISAM. In this version the, template comprises three elements: Data Specification Sheet, ML Model Specification Sheet and ML Model Summary Findings.},
+    }
+
+
+%software platform
+@InProceedings{EPandRP,
+      title       = {FG-AI4H Open Code Initiative - Evaluation and Reporting Package},
+      author      = {Elora Schörverth and Steffen Vogler and Pradeep Balachandran and Alixandro Werneck Leite and Danny Xie Li and Kamran Ali and aAndrea Garcia and Dominik Schneider and Joachim Krois and Marc Lecoultre and Shobha Iyer and Shruti Choudhary and Luis Oala},
+      booktitle = 	 {Proceedings of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H) - Meeting K},
+      institution = {International Telecommunications Union},
+      address     = {Geneva, Switzerland},
+      number      = {FGAI4H-K-043-A01},
+      year        = {2021},
+      month       = {January},
+      abbr={ITU/WHO},
+      html={https://extranet.itu.int/sites/itu-t/focusgroups/ai4h/_layouts/15/WopiFrame.aspx?sourcedoc=%7BD810F149-A5D1-4380-B128-5AC4F8AC07EC%7D&file=FGAI4H-K-043-A01.pptx&action=default&CT=1614792781425&OR=DocLibClassicUI},
+      pdf={standards/FGAI4H-K-043-A01.pdf},
+      abstract={Presentation of the software components developed by WG-DAISAM for automating the FG-AI4H evaluation process.},
+      code={https://github.com/aiaudit-org/fgai4h-evaluation-platform}
+    }
+
+
+%din
+@InProceedings{report-template,
+      title       = {TODO},
+      author      = {Last, First and Last, First ...},
+      institution = {TODO},
+      address     = {CITY, STATE, COUNTRY},
+      number      = {TODO},
+      year        = {1900},
+      month       = {},
+      abbr={TODO},
+      html={TODO},
+      pdf={TODO},
+      abstract={TODO},
+      code={TODO}
+    }
+

_includes/selected_papers.html

@@ -1,4 +1,4 @@
 <div class="publications">
-  <h2>Selected publications</h2>
+  <h2>Selected outputs</h2>
   {% bibliography -f selected -q @*[selected=true]* %}
 </div>

_layouts/about.html

@@ -29,9 +29,11 @@ <h1 class="post-title">
       {{ content }}
     </div>
 
+    <!-- 
     {% if page.news %}
       {% include news.html %}
     {% endif %}
+    -->
 
     {% if page.selected_papers %}
       {% include selected_papers.html %}

_news/test-news.md

@@ -0,0 +1,8 @@
+---
+layout: post
+date: 2021-03-10
+title: Test news
+inline: false
+projecttag: measuresandmetrics
+---
+Some content

_pages/about.md

@@ -12,42 +12,30 @@ news: true  # includes a list of news items
 selected_papers: true # includes a list of papers marked as "selected={true}"
 social: false  # includes social icons at the bottom of the page
 ---
-# THIS SITE IS UNDER CONSTRUCTION (:
-
-# Context
 aiaudit.org is a collaborative research network formed under the auspices of the Data and AI Solutions Assessment Methods (DAISAM) WG, which is one of the core working groups under the ITU/WHO Focus Group on “AI  for Health” ([FG-AI4H](https://www.itu.int/en/ITU-T/focusgroups/ai4h/Pages/default.aspx)) . The Focus Group which was established in July 2018 works in partnership with the World Health Organization (WHO) to establish a standardized assessment framework for the evaluation of AI-based methods for health with primary focus on quality of care and patient safety. 
 aiaudit.org network brings in the expertise and experience of a global multidisciplinary group of stakeholders that include machine learning/AI researchers, data scientists, clinical specialists, healthcare practitioners and researchers, medical device manufactures and consultants, regulators, software developers, and individuals from allied and complementary fields.
 
+TODO: link to all the menu items in the above text
+
+{% if page.news %}
+  {% include news.html %}
+{% endif %}
+
+## Vision
 <div class="row">
     <div class="col-sm mt-3 mt-md-0">
         <img class="img-fluid rounded z-depth-1" src="{{ '/assets/img/eval-process.jpg' | relative_url }}" alt="" title=""  width="768" height="432"/>
     </div>
 </div>
+<br/>
 
-# Vision
-- To facilitate a cross-functional collaborative platform for stakeholders to develop a consensus driven AI audit standardization framework
-
-- To promote stakeholder education and awareness on the adoption and dissemination of good AI audit practices to support regulatory conformity assessment of market-driven AI based solutions
-
-# Values
-
-
-# Colloborative Research Projects
-aiaudit.org is currently driving 5 R&D projectsas listed below:
-1.	Perturbed minds (research)
-2.	Model reporting questionnaire (research)
-3.	Evaluation platform (software development)
-4.	Regulatory Good practices (regulatory)
-5.	ML4H “ICD-10”(regulatory)
-
-
-# Tools and Resources
+* To facilitate a cross-functional collaborative platform for stakeholders to develop a consensus driven AI audit standardization framework
 
-# Publications and Contributions
+* To promote stakeholder education and awareness on the adoption and dissemination of good AI audit practices to support regulatory conformity assessment of market-driven AI based solutions
 
-# Groups and Institutions
+## Values
+Colloborative Research Projects
 
-# License
 The content of this website is published under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).
 
 Short teaser text with the different areas of the menu being introduced (see miro)

_projects/measures-and-metrics.markdown

@@ -1,18 +1,25 @@
 ---
 layout: page
-title: Measures & Metrics
-description: Collection of SOTA ML quality assurance methods like bias, generalizations, robustness, uncertainty, and so forth about use cases and regulatory topics.
-img: /assets/img/m&m.png
-contact: Luis Oala ([email protected]) and Pat Baird ([email protected])
-coordinates: Every Thursday, 2:00 PM, Geneva Time
+title: Measures & Metrics #a project title as it will appear on the website
+img: /assets/img/IMDRF-ICD.png #thumbnail logo for the project overview
+img2: /assets/img/IMDRF-ICD.png #a second banner for the second half of the page, contents of this banner should be related to the work stream
+worktype: bg-success #select one of the colors (researchandmethods: bg-success, standardizationandregulation: bg-primary, softwaretooling: bg-info)
+lifecyclesteps: 1 2 3 4 #select one or more of the numbers for the life cycle steps 1 2 3 4
+description: Collection of SOTA ML quality assurance methods like bias, generalizations, robustness, uncertainty, and so forth about use cases and regulatory topics. #a very short description of
+projecttag: measuresandmetrics #use this tag as the name for your project .bib file
+contact: Luis Oala, [email protected] #Firstname Lastname, email of the general contact
+coordinates: Every Thursday, 2:00 PM, CET #Interval and day, HH:MM PM, time zone
+zoomroom: #link to the zoom room that is used for meetings
+groupchat: #invite/access request link to the group chat
+mailinglist: #email of the mailing list that people can subscribe to for this workstream
+github: #provide a github link for the project if it exists
+whiteboard: #link to the miro whiteboard that is used for the work stream
+drive: #link to the shared drive of the work stream (for documents etc)
 importance: 2
-worktype: bg-success
-lifecyclesteps: 1 2 3 4
-github: 
 ---
 <div class="row">
     <div class="col-sm mt-3 mt-md-0">
-        <img class="img-fluid rounded z-depth-1" src="{{ '/assets/img/IMDRF-ICD.png' | relative_url }}" alt="" title="" width="{{ site.max_width }}" height="100"/>
+        <img class="img-fluid rounded z-depth-1" src="{{ page.img | relative_url }}" alt="" title="" width="{{ site.max_width }}" height="100"/>
     </div>
 </div>
 <br/>
@@ -27,62 +34,75 @@ We already developed a paper about Machine Learning for Health Audit in this wor
 #### Aims
 Develop better regulations by publications, international standards about measures, and metrics inside Machine Learning for Health.
 
-#### Planned Outputs
-* Regulatory documents about measures & metrics inside of Machine Learning.
-* Paper about bias, robustness, uncertainties and other aspects of M&M in ML4H.
+#### Outputs
+<div class="publications">
+  {% bibliography -f {{ page.projecttag }} -q @*[projectoutput=true]* %}
+</div>
 
 ---
 # Collaboration resources
 You are welcome to inquire about the work stream and opporunities for collaboration directly with the work stream team.
-* **General contact**
+* **General contact** {{ page.contact }}
 
 #### Meetings
 Regular meetings for this work stream take place at the below coordinates. 
-* **Meetings** Thursdays, 16.00 hrs, Geneva
-* **Zoom room**
+* **Meetings** {{ page.coordinates }}
+* **Zoom room** [Click here to join meeting]({{ page.zoomroom }})
 
 #### Communication
 You can subsbscribe to the work stream mailing list to receive updates and join the asynchronous group chat.
-* **Group chat**
-* **Mailing list**
+* **Group chat** {{ page.groupchat }}
+* **Mailing list** {{ page.mailinglist }}
 
 #### Tools
 We use different tools in our remote work. They include shared documents, github projects for code as well as task tracking and a collaborative whiteboard for ideation. You can request access via the below links.
-* **Shared document**
-* **Github project**
-* **Collaborative whiteboard** 
+* **Shared drive** {{ page.drive }}
+* **Github project** {{ page.github }}
+* **Collaborative whiteboard** {{ page.whiteboard }}
 
 You can find more information about the way we usually carry out our work remotely in teams [here](https://aiaudit.org/join).
 
 ---
 
 # Milestones
-
 <div class="news">
   {% if site.news  %}
     <div class="table-responsive">
       <table class="table table-sm table-borderless">
       {% assign news = site.news | reverse %}
       {% for item in news limit: site.news_limit %}
-        <tr>
-          <th scope="row">{{ item.date | date: "%b %-d, %Y" }}</th>
-          <td>
-            {% if item.inline %}
-              {{ item.content | remove: '<p>' | remove: '</p>' | emojify }}
-            {% else %}
-              <a class="news-title" href="{{ item.url | relative_url }}">{{ item.title }}</a>
-            {% endif %}
-          </td>
-        </tr>
+        {% if item.projecttag == page.projecttag %}
+            <tr>
+            <th scope="row">{{ item.date | date: "%b %-d, %Y" }}</th>
+            <td>
+                {% if item.inline %}
+                {{ item.content | remove: '<p>' | remove: '</p>' | emojify }}
+                {% else %}
+                <a class="news-title" href="{{ item.url | relative_url }}">{{ item.title }}</a>
+                {% endif %}
+            </td>
+            </tr>
+        {% endif %}
       {% endfor %}
       </table>
     </div>
   {% else %}
 
   {% endif %}
 </div>
-TODO: news filtered with project slug
 
-# Related work and resources
-This is a list of related work and resources relevant for this work stream.
-TODO: ref with tag
+<div class="row">
+    <div class="col-sm mt-3 mt-md-0">
+        <img class="img-fluid rounded z-depth-1" src="{{ page.img2 | relative_url }}" alt="" title="" width="{{ site.max_width }}" height="100"/>
+    </div>
+</div>
+<br/>
+
+# Important reference material
+This is a list of related work and resources relevant for this work stream. It comprises resources the work stream contributors consider good practice.
+
+<div class="publications">
+  {% bibliography -f {{ page.projecttag }} %}
+</div>
+
+

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