va?rsta-creierului-ca?t-mai-ai-de-tra?it.png

SEMINAR PROFILE

 

Period                                   March 8-10, 2019
Place                                    Google Japan
                                             (Roppongi Hills, 6-10-1 Roppongi, Minato-ku, Tokyo  106-6108, Japan)  
Representative Organizer       Satoru Hashimoto, MD (Kyoto Prefectural University of Medicine)
*Hands-on Workshop will be also held on March 7, 2019 at the TMDU as the supplemental program.

NEC

 

Japan’s Second Big Data
Machine Learning Event in Healthcare

 

 It is my great pleasure to announce our second medical big data analytics conference in Japan, which we will host at the Google Japan Tokyo office during March 8 to 10, 2019. Our first conference at Tokyo Medical and Dental University (TMDU) in 2018 was largely successful and ignited great enthusiasm among experts from industry and academia, as well as among students. For our second event, we anticipate many data scientists and critical-care experts to gather in Tokyo and decipher big data extracted from various ICU-derived electronic medical records. We will also host a hands-on workshop on March 7 at TMDU as an introductory session and side event to the conference.
 At our first Datathon at TMDU, it was amazing to see many participants that initially did not know one another instantly connect. By the end of the event, many had become so close, remaining in contact to develop new projects and partake in ongoing collaborative research.
 For our second conference, the steering committee and I will host a full Datathon, inviting experts from the United States, Australia, New Zealand, and Singapore, alongside other newcomers. We hope this event will catalyze the development of an integrated multidisciplinary team of healthcare professionals, data scientists, system engineers, statisticians, industries, venture capitalists, and other professionals. Our ultimate goal is to work as a team to optimize patient care at the bedside by effectively utilizing artificial intelligence and machine learning with big data. We look forward to welcoming you all to Japan.

Satoru Hashimoto, MD
Professor, Director of Intensive Care Division
Department of Anesthesiology and Intensive Care Medicine
Kyoto Prefectural University of Medicine, JAPAN

 2019年3月8日から3日間、東京六本木ヒルズ Google Japan東京オフィスにて第2回のBig Data and Machine Learning in Healthcare in Japanを開催させていただくことになりました。今回は会場が手狭なため60名程度しかDatathon(3月9日10日の2日間)に参加いただけないため、3月7日に東京医科歯科大学構内にて技能別のハンズオンワークショップも企画しております。
 2018年2月24-25日に東京医科歯科大学で開催した第1回のBig Data and Machine Learning in Healthcare in Japanは多くの皆様のご協力により盛会となり成功裏に終会しました。それまで面識のなかった統計学者と臨床医が二日間という短い期間ではありましたがお互いを知ることとなり、多くの方が1年後の再会を約して下さいました。当初は私の本拠地である京都での開催を考えましたが、過去に本イベントを全面的に支えておられるGoogle社のご厚意により東京六本木の本社にて開催することに急遽変更させていただきました。このためご案内や若干募集等の開始が遅れ、また募集総数が少なめになってしまったことはご容赦ください。
 医療において、電子カルテをはじめとしたデジタル化の波は今後も前進しつづけることは間違いありません。そこで蓄積されるbig dataをいかに利活用するかが、これからの医療において重要な意味を持つことは誰の目にも明らかです。一方、医療者だけではこのようなbig dataを処理しそこから意味ある結論を導くことはますます困難になってきているのではないでしょうか? データソンはこのようなbig dataの解析における、AI machine learning活用に長けるdata scientistsと医療従事者との出会いの場です。春間近の六本木にて皆様をお待ち申し上げます。

橋本 悟
集中治療部 部長/病院教授
京都府立医科大学附属病院

 
Screen Shot 2018-07-31 at 21.34.50.png
IMG_1661.JPG

What is a Datathon?

 A Datathon per se is a voluntary, sprint-like event in which data scientists and experts in a certain field gather and work side by side with the aim of tackling major questions in the field through the analysis of big data. It is typically organized in the way of a competition with many concurring teams, and often held on a weekend. ICU Datathons do not differ much from this general model: teams composed by physicians, data scientist, statisticians and engineers are formed and all attempt to solve some of the current issues in the Intensive Care Unit (ICU) using the data from MIMIC Database, ANZICS APS, or JIPAD. The themes (clinical questions) are proposed by physicians, usually members of the national ICU society of the hosting country, before the actual Datathon takes place, while the teams are built just prior or at the event itself.
 Second Datathon in Japan will be held from Friday, 8th of March 2019 to Sunday, 10th of March. The first day will offer hands-on workshops and lectures. Saturday and part of Sunday will be for “hacking”, which in a health Datathon means the application of machine learning on health data. Participants with various backgrounds will work together with the shared goal of addressing a research question. At the end of Sunday, teams present their analyses. A Scientific Committee will select and award the best 3 projects based on clinical relevance, the novelty of the topic, the methodology, and the quality of the presentation.
 The IT infrastructure is managed by the experts from Massachusetts Institute of Technologies and National University of Singapore and other societies. A team coming from various Japanese institutes takes care of setting up the database and the connections to the servers. These facilitators also provide support to the various teams during the competition.
 The event is sponsored by companies and institutions. In past Datathons, companies like Google, Philips, General Electric, Hitachi and others (see past events) were involved with their national and international representatives.

How does it work?

 The opening ceremony is usually held by the members of the MIT Team, who welcome the participants, introduce the rules and the subject of the event, and explain all the tools and databases available during the competition.
 The teams are then formed and assigned a clinical task: the modalities in which this is brought to completion vary. The core of the Datathon is the hacking phase, which takes place from Saturday morning through Sunday afternoon. Teams thus have less than 2 days to tackle the clinical question they were assigned. Afterwards, they are asked to present their results in front of both the public and judges. The board decides and announces the winning team and runner-ups during the closing ceremony where they are presented with their awards. The goal of the Datathon is ultimately to create interdisciplinary collaborations in critical care as well as promoting the use of advancing machine learning techniques in healthcare.
 Before and/or during the competition, MIT experts, invited speakers and exponents from companies and institutions engage in presentations and talks about the subject, making up for the conference part of the event. This is usually held on Friday.

PROGRAM

day 1

Coming soon


Day 2

Coming soon


Day 3

Coming soon

 

REGISTRATION

Those who would like to join the 2nd Big Data Machine Learning in Healthcare in Japan are requested to apply in advance before completing the registration by paying the registration fee.

> For Japanese participants:
   日本人の方は下部日本語申込フォームからお申し込みください。

※The pre-Datathon event, that is the trial seminar for training for the 2nd Datathon, is planned to have on January 12, 2019 at the TMDU. The registrants can join this pre-event for free (Pre-registration is required.).

Registration Category

◆Course 1: Lectures (March 8, 2019@Google Japan)

Registration fee
<Physician>5,000 JPY
<Other professionals & student>2,000 JPY
<Industry staff>5,000 JPY
Capacity
30 persons

◆Course 2: Hands-on Workshop (March 7, 2019@TMDU/Portable WiFi required) + Lectures (March 8, 2019 @Google Japan)

Registration fee
<Physician>15,000 JPY
<Other professionals & student>5,000 JPY
<Industry staff>15,000 JPY
Capacity
60 persons

◆Course 3: Lectures (March 8, 2019@Google Japan) + Datathon Workshop (March 9 & 10, 2019 @Google Japan)

Registration fee
<Physician>30,000 JPY
<Other professionals & student>10,000 JPY
<Industry staff>50,000 JPY
Capacity
60 persons

*Those who would like to attend the Hand-on Workshop on March 7, please ask the availability.

How to register

  1. Application:
    Click the ‘APPLY’ and complete the Application Form before December 15, 2018.
  2. Selection:
    In case of oversubscription, we will select participants in the capacity according to the occupation, affiliation and/or other backgrounds.
  3. Notification:
    Result of selection will be announced with the URL for the Registration Form by email before December 31, 2018.
  4. Registration:
    Fill in the Registration Form.
    Complete the registration by remitting the registration fee by credit card.
    Completion notice will be received with the information of MY PAGE. In MY PAGE, you will find the QR code and the tentative receipt. Your personal data and log-in password can be changed.

How to participate

  1. Print out and show your QR code at the Reception Desk and receive the name card.
  2. Be sure to wear your name card during the event.
    *Please bring your own PC.

APPLY

参加申込

2nd Big Data Machine Learning in Healthcare in Japanは定員制です。参加していただくには、参加費お支払いの前に、まずご応募ください。

※Datathonに向けて予習していただく目的で、2019年1月12日(土)に東京医科歯科大学において2nd Datathonのプレイベントを開催する予定です。2nd Datathon参加者は無料でご参加いただけます(事前申込制)。

参加種別

◆コース1:講演(3月8日(金)/Google Japan)

参加費
<医師> 5,000円
<その他(学生を含む)> 2,000円
<企業関係者> 5,000円
定 員
30名

◆コース2:ハンズオンワークショップ(3月7日(木) /東京医科歯科大学/ポケットWiFi持参要)+講演(3月8日(金)/Google Japan)

参加費
<医師> 15,000円
<その他(学生を含む)> 5,000円
<企業関係者> 15,000円
定 員
60名

◆コース3:講演(3月8日(金)/Google Japan)+ Datathonワークショップ(3月9日(土)・10日(日)/Google Japan)

参加費
<医師> 30,000円
<その他(学生を含む)> 10,000円
<企業関係者> 50,000円
定 員
60名

※企業にお勤めの方で、個人として参加をご希望の場合は、ご相談ください。

申込方法

  1. 下記「APPLY」ボタンをクリックし、応募フォームに必要事項をご入力ください。
    応募期限: 2018年12月15日(土)

    *データサイエンティストの方は、「職種」欄で「その他」も選び(複数選択可)、「職種「その他」を選択した方」欄にデータサイエンティストである旨ご記入ください。

  2. 定員を超えた場合、職種やご所属、ご活躍分野等を考慮して選抜させていただきます。
  3. ご参加いただけるかどうかを2018年12月末日までにお知らせします。
  4. 参加登録URLをお知らせしますので、必要事項をご入力いただき、参加費をお支払いください(クレジット決済のみ)。
    申込完了通知メールが届きます。マイページへのログイン情報が記載されております。
    マイページには参加の際に必要なQRコードが表示されているほか、仮領収書の発行や個人情報、ログイン用パスワードなどの変更が可能です。

参加方法

  1. マイページに表示されているQRコードを印刷し、参加受付でご提示ください。名札をお渡しします。
  2. 会議中は必ず名札をご着用ください。
    *当日は各自PCをご持参ください。

事前準備のお願い

本ワークショップの一部で使用するAnacondaについては、事前に各自のPCにインストールしていただくようお勧めします。インストールは簡単です。ネットワーク環境のよい状態であれば20−30分程度で完了します。ぜひ当日までにご対応ください。
  ➡方法はこちら: Windows user Mac user

また、当日までにGitHubの無料アカウントを取得しておいてください。すでに無料、有料アカウントをお持ちの方は結構です。
  ➡登録はこちら

APPLY

 
 

Speakers & Facilitators

Coming soon

SPonsorship

Prospectus for sponsorship: here

ACCOMMODATIONS

Coming soon

Past Datathons

DSC_0660.jpg

Madrid

December 1-3, 2017

The event was held in a coworking space (the Impact Hub Madrid) where every team had its own area to develop their projects. The event began on Friday with a series of talks from MIT experts, European researchers and clinician as well as institution representatives. On Saturday, there were talks from companies such as Philips followed by a team-building phase. The Spanish national ICU society and the MIT committee selected the projects, emphasizing topics that reflected the actual needs in the European landscape. The rest of Saturday and the whole of Sunday were reserved to the actual “hacking” phase. The event ended with final presentations from the various teams, judgement from the board and an awards ceremony.

DUFFuEBW4AAmMKq.jpg

Paris

January 20-21, 2018

Unlike Madrid, the project proposals and team-building phase started twenty days before with groups from Google and completed a week before the Datathon. On Saturday morning clinicians from the MIT-LCP, the APHP and the French ICU society opened the event and introduced the tools that were available for project development. Also, it was at this event that the APHP database was unveiled: the first European online database that resembles MIMIC and currently the biggest medical aggregation. The Datathon ended on Sunday with a talk from Hitachi followed by an awards ceremony. Of note, Google was involved in the MIMIC – OMOP development and was also represented as a team in the competition.

Video review of the event: https://youtu.be/cxFsCkGGpYE

IMG_2561.jpg

Tokyo

February 24-25, 2018

The 1st Big Data Machine Learning in Healthcare Datathon in Japan was held at the Tokyo Dental and Medical University following the Japanese Society of Intensive Care Medicine's Annual Congress. This two day conference first held in Japan was comprised of seven lectures, 11 hands-on workshops, and a mini-Datathon (half day version of the Datathon style workshop). Participants from various sectors, from students and professionals in healthcare related fields to programmers, gathered to analyze data from MIMIC, the ANZICS APD (adult patients database), and JIPAD (Japanese ICU patients database) to answer six prefixed clinical questions, with one winning team selected at the end of the event. Collaborative efforts for publications have continued beyond the Datathon and we look forward to seeing more during our second year.