5th Digital Pathology & AI Congress: USA

When

2019年6月13-14日

Where

美國,紐約
Stewart Hotel

5th Digital Pathology & AI Congress: USA
-第5屆數位病理學暨AI年會:美國大會-
日期:2019年6月13-14日
地點:美國,紐約,Stewart Hotel
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5th Digital Pathology & AI Congress: USA

藉由數位病理學及人工智慧(AI)的活用而進步的病理診斷及病患照顧的改善

Global Engage延續在數位病理學主題學會的成果、第5屆Digital Pathology & Al Congress USA、2019年6月13日至14日將在美國紐約市舉行。

美國近年來用於影像解析的AI等有望技術陸續受到開發,可將病理診斷數位化的Philips IntelliSite Pathology Solution獲得FDA核可,數位病理學一炮而紅。此外病理全切片影像分析、自動分析法、遠距醫療諮商等領域也持續進化,病理診斷領域中,對新技術登場所帶來的革命性變化之期待也隨之高騰。

數位病理多樣領域相關專家集結,本年會包含了利用AI與機械學習的數位影像處理技術、影像分析法的新進步、針對導入AI到病理診斷的措施進行50分鐘雙向意見溝通等時段,以數位病理的導入與實用化,以及成功實現工作流程的策略等主題單元也將在為期2日的會議期間登場。

2019年主要演講者

> 演講者名單

概要

  • 由藥廠幹部及主要研究人員發表30場以上的演講。
  • 各種交流活動總時間將超過7小時。
  • 兩場高階幹部的專題討論。
  • 9場小組討論。
  • 聚集眾多數位病理領域的技術及解決方案供應商的展示會。
  • 海報發表及海報比賽。
Find out more

演講者

2019年演講者

小型會議

Pre-Conference Site Visit: Memorial Sloan Kettering Cancer Center Tour

When

2019年6月12日

Where

美國,紐約
Memorial Sloan Kettering Cancer Center

Memorial Sloan Kettering Cancer Center Site Visit

Wednesday 12th June 2019 - For Registered Participants Only

Numbers strictly limited. Available on a first come first served basis. Time slot for your site visit will be allocated at least two weeks before the event.

Tours will take place at:

Session 1 – 9am – 10.30am 

Session 2 – 11am – 12.30 pm

Session 3 – 2pm – 3.30pm

Session 4 – 5pm – 6.30pm

* 活動內容有可能不事先告知作更動及調整。

Pre-conference workshop: Aiforia

When

2019年6月12日
5pm-9pm

Where

美國,紐約
Stewart Hotel

Demystifying Deep Learning AI and Digital Pathology:

Demystifying Deep Learning AI and Digital Pathology:

DEMOCRATIZING AI AND EMPOWERING THE PATHOLOGIST

Your one-stop workshop will help you to understand and deploy intelligent solutions with ‘Aiforia Create’ Deep Learning Pathology. With a hands on experience to ensure you are trained to achieve precise active annotations and understand how different annotation mistakes affect your results.

The hands-on part is run as a friendly competition and the lowest error rate walks away with a prize and bragging rights.

Takeaways

  • A road map for implementation of Deep Learning solutions for your Digital Pathology workflow.
  • A deep understanding for the importance of ‘high quality, not high quantity’ of training data.
  • Understand how to structure algorithms,
  • Train your own Deep Learning Neural Network, Live, On the Premises.

Join the discussion and share your thoughts and ideas with us and the invited guest speakers

3 TALKS

Thomas Westerling-Bui, Ph.D. , Senior Scientist, Aiforia Inc

Digital Pathology for drug development in the age of unlimited analysis design possibilities

Automated analysis can improve precision and recall, as well as reduce inter- and intra-operator differences. This leads to increased effect size and likelihood to get a measure of the true effect size of an experimental drug treatment.

Gillian Beamer, Assistant Professor, Tufts University

End user developed Deep Learning algorithms for the analysis of Lung granulomas in experimental tuberculosis.

Exploring the utility of domain expert driven Deep Learning algorithms to study Host Response to virulent M. tuberculosis including algorithms to delineate and segment granuloma and necrosis in hematoxylin and eosin (H&E) stained lung tissue from M. tuberculosis-infected Diversity Outbred mice.

  • Examples of user generated Deep Learning algorithms in pre-clinical research models.
  • Paths to algorithm validation
  • Path to deploying Create for yourself or your team

Peter Westcott, Postdoctoral fellow, Koch Institute for Integrative Cancer Research

Deep neural network for automatic histopathological analysis and grading of murine lung tumors

A demonstration that deep neural networks can be used for automated analysis and grading of preclinical models of lung cancer and an exploration of how this powerful technology has the potential to increase the throughput, sensitivity and reproducibility of hypothesis-driven studies of factors influencing tumor progression and immune response in mouse models of lung cancer.

  • What happens when an entire lab at MIT uses one unifying digital pathology algorithm instead of multiple individual human operators.
  • Development of a tumor grading algorithm that is robust against known usual tissue artefacts.
  • Paths to Algorithm Validation

* 活動內容有可能不事先告知作更動及調整。

Pre-conference workshop: Akoya Biosciences

When

2019年6月12日
12pm-4pm

Where

美國,紐約
Stewart Hotel

Phenoptics 2.0 with MOTiF
Enabling Better Spatial Biomarker Discovery

 

Multiplex immunofluorescence (mIF) assays have enabled the assessment of complex biological interactions between cellular phenotypes within their native microenvironments. However, regardless of plexing level, the quantitative analysis of mIF tissue sections and tumor microarrays is typically made challenging by the co-localization of signals of interest, by spectral cross-talk between fluorophores, and by the presence of autofluorescence. Whole Slide Multispectral Imaging (MOTiF) is a powerful imaging tool that address all of these challenges, permitting visualization, analysis, and accurate quantification of specific biomarkers on a per-cell basis, along with techniques that enable the phenotyping of an extremely wide variety of cell types in situ in solid tissue. What’s more, it enables the quantification of weakly expressing and overlapping biomarkers within cells and cellular compartments that cannot be identified using traditional imaging and analysis techniques, as well as the ability to isolate autofluorescence from desired signal. A growing body of work indicates that the use of multispectral unmixing in the analysis of mIF assays results in improved understanding of the underlying biology of disease and permits more accurate quantification of the relationships between specific cell types.

Takeaways:

  1. The challenges associated with quantitative immunofluorescence in intact FFPE tissue sections and TMAs
  2. A deep understanding of how multispectral unmixing isolates desired signal from background autofluorescence
  3. The relationship between fluorophore plexing level and visualization of underlying biology within tissues
  4. How phenotypic spatial metrics can enable better prediction of immunological therapeutic responses

 

Speakers

Daniel Eversole, PhD (Product Manager, Phenoptics Software, Akoya Biosciences)

Valeria Mezzano, MD, PhD (Research Scientist, Department of Medicine, NYU Langone Medical Center)

Michael Surace, PhD (Scientist II, AstraZeneca)

Dan Walker, (Product Manager, Phenoptics Instruments, Akoya Biosciences)

Linden Wyatt, PhD (Technical Application Scientist, Akoya Biosciences)

* 活動內容有可能不事先告知作更動及調整。

議程

集結了數位病理多樣領域專家的本年會,預定了數位影像分析領域中AI的使用及3D影像解析等影像分析主題環節,以及聚焦於數位病理導入實務與個案研究介紹的環節,都將在為期2日的會議期間登場。

Digital Pathology & Al Congress在歐洲、美國、亞洲皆有舉辦的年會活動,聚集來自59個國家超過2500位病理學專家。

2019年重點

為了回應過去與會者的要求,本屆年會新增了針對醫療從業人員的AI介紹工作坊。本工作坊可讓與會者深入了解AI及其在病理診斷方面的應用潛力與現狀,由Rutgers-NJMS生物物理學病理診斷中心第一任所長兼賓州大學病理學名譽教授Stanley Cohen主持進行。

Download the Agenda (PDF)

贊助商

2019年贊助商

贊助商名單

地點

Stewart Hotel

371 7th Ave, New York, NY 10001, USA

海報發表

海報發表不僅在休息時間進行,也會與分科會討論同時進行。所有藥廠或研究機構的研究人員所製作的海報,都必須在獲得學會事務局許可後張貼於會場內指定區域。

此外,學會閉幕後,將發給所有出席者匯集海報發表大綱的電子書,亦可將海報以.pdf形式的檔案公開(僅限意者)。

海報發表對於尋求出資和雇用機會的人,以及希望在志同道合、研究同一題目的研究者團體中發表成果的人來說,是能夠在會場內廣受矚目的珍貴機會。

必須報名參加本年會方可進行海報發表。張貼海報的空間有限,將依報名順序接受通過審查者張貼海報,故建議盡早申請。

海報發表比賽申請期限至:5月10日

  1. 請於報名期限內申請報名(每人僅限一件)。
  2. 經審查後在全體共同舉行的會議之中選出2位優勝者。
  3. 海報比賽的優勝者可在主要研討會中發表15分鐘的演講。優勝者將事前獲得通知。
  4. 評審將根據海報摘要進行評選。
  5. 優勝者將由主辦單位頒發獎狀。
  6. 本年會以英語進行。
  7. 隸屬於解決方案供應商者,雖無法參與報名比賽,但仍可在會場內發表海報。

海報發表報名辦法

請填寫專用表格(點擊下列連結下載)於2019年5月10日以前繳交。若只想發表海報而無意參加比賽,則報名期限為5月24日。若於截止日期前額滿將提早截止報名,敬請儘早申請。詳情歡迎與我們聯繫。

贊助商

2019年 贊助商

上屆會議迴響

Perfect talks

I liked the program and the speakers. The length of the talks and amount of material was perfect. I liked the mix of biotech, company and academic speakers. I also liked the collegial and friendly atmosphere during the meeting.

Beatrice Knudsen

Professor, Biomedical Sciences and Pathology and Laboratory Medicine, Director, Translational Pathology, Cedars Sinai Medical Center

Engaging speakers

There was a wide range of speakers, perfect amount of time per topic and good mix of short and long sessions. The speakers were engaging and truly spoke to audience across pretty diverse fields.

Erin Brannick

Assistant Professor, Director of Comparative Pathology Laboratory, Department of Animal & Food Sciences, University of Delaware, USA

Great mix

There was varying lecture content - a mixture of technical and research, and the inclusion of a FDA spokesperson to clarify some of the issues.

Kathleen Whitney

Attending Pathologist, Montefiore Medical Center, USA

Excellent opportunity

I liked the mix of image scientists, pathologists and companies. It was an excellent opportunity to meet a diverse group in digital pathology.

Lenore McMackin

President & CTO at InView Technology Corporation, USA

贊助商募集

藉由成為本年會的贊助商或參展者,可在融洽的氣氛中,與各組織的代表於各種正式、非正式的場合進行會談,建立合作關係的機會。

本年會準備了各種贊助方案,豐富的選項可配合您的業務需求自由搭配,以獲取最大額度的投資報酬。

欲採其他方式贊助本學會者,或考慮進行方案規畫者,歡迎隨時與本會洽詢。本會將提出合乎個別需求的服務建議。

可事先預約的20分鐘個別會談時段

贊助商與參展者可以事先預約在主要研討會的分科會會議中排定的20分鐘個別會談時段,與希望的對象見面。會期中,Global Engage團隊會常駐會場,協助會談按時進行。

年會前後的研討會

可在年會前後以對特定主題感到興趣者為對象,舉辦為期半天或全天的工作坊活動。Global Engage將協助宣傳以確保工作坊達到足夠的出席人數。

年會開幕前的行銷與宣傳

利用Global Engage的資料庫展開行銷活動,透過海報張貼、休息與午餐會、酒會、贊助海報發表等提高品牌知名度。另備有追加項目可將貴公司的logo印製在發放給與會者的名牌吊繩與年會資料包上。

參展

會議期間設有專用的展示區域,可向所有的與會者展示您的技術與產品。展示區域將設於休息及午餐會,以及第一天晚上的歡迎酒會的舉辦場所。

演講

發言的型態

  • 30分鐘演講
  • 在30分鐘專題討論中擔任主持人或討論人員
  • 在年會議程中舉行一小時的研討會
募集贊助商

歡迎來信或來電與日商環球訊息有限公司台灣分公司聯繫。

包括簽證等各種海關所需文件,以及展示用品的通關手續皆由展商企業各自負責。

展示相關的安排(企業介紹、公司商標、提供與會者目錄中的展商資訊登錄、展示空間的裝潢、用品訂購、展示用品的擺設搬運、展示空間的文件申請、保險等)請直接與主辦方連繫。

旅遊相關疑問(住宿、機票)、當地翻譯人員、飛行與意外保險等問題,將有另外的專門業者分別提供服務。

關於Digital Pathology & Al Congress: USA的贊助商詳情,請洽本公司。

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