27 posts found

May 2022 Cycle Report

5 July 2022 by Miriam Groeneveld

Highlights include viewing a reader's answers, providing default answers for questions in a reader study, starting a reader study at a specific display set and more.

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What's up in AI for Radiology - June 2022

30 June 2022 by Kicky van Leeuwen

New fracture detection AI | Us2.ai newest player in EU | Scarce pediatric and real-world studies | ESR practical experience survey | and more

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What's up in AI for Radiology - May 2022

31 May 2022 by Kicky van Leeuwen

MDR and buying AI - what to consider | MammoScreen, Quantib Prostate and GIQuant next steps | Five validation studies | DECIDE-AI | and more

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One year of MDR: 17% of products comply

27 May 2022 by Kicky van Leeuwen

It has been a year since the more stringent Medical Device Regulation (MDR) replaced the former Medical Device Directive (MDD). With two years left on the clock for the 'transition period', only 17% of the AI products for radiology have obtained clearance under the MDR so far. If the market continues at this pace, half of the current CE marked AI products for radiology will not comply in time. The likely consequence is that software will be taken off the market and can no longer be used clinically after May 2024. Does that mean users stop buying MDD compliant AI software? Read about it in this blog!

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AIROGS Challenge Report: AI models can be used for glaucoma screening, but do they know when they cannot?

10 May 2022 by Coen de Vente, Bram van Ginneken, Megan Schuurmans, Clarisa Sanchez and Hans Lemij

The rationale behind the Artificial Intelligence for RObust Glaucoma Screening (AIROGS) Challenge, an overview of its results and our experiences with Grand Challenge's new Type 2 challenges.

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What's up in AI for Radiology - April 2022

29 April 2022 by Kicky van Leeuwen

Is AI replacing radiologists? | FDA warns for stroke AI | icobrain ms assessed | Welcoming Ligence and BrainTale | and more

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Spring Newsletter 2022

11 April 2022 by Megan Schuurmans, Anne Mickan, Joeran Bosma, Kiran Vaidhya Venkadesh, Bram van Ginneken, Khrystyna Faryna and Daan Schouten

Hi all! With this newsletter we want to update you on all progress made for Grand Challenge: new features, interesting new blogposts and algorithms, upcoming challenges and the leaderboards of finished challenges.

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What's up in AI for Radiology - March 2022

30 March 2022 by Kicky van Leeuwen

Newsletter anniversary | EU Data Space regulation | FDA clearance for GLEAMER and annalise.ai | Welcoming CASIS, Qynapse, Monitor and Koios | many new validation studies | and more

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Can AI predict breast cancer recurrence via automated quantification of tumor-infiltrating lymphocytes?

6 March 2022 by Francesco Ciompi, Anne Mickan, Bram van Ginneken, Alexander Lemm, Roberto Salgado and Megan Schuurmans

TIGER is the first challenge on fully automated assessment of tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) breast cancer histopathology slides. With TIGER, we released a training set of 390 whole-slide images and a total award of $13,000 in AWS Credits, which will be awarded to the winning teams. Together with its participants, we aim to find the best AI-based solutions for automating the assessment of the TILs and produce a “TILs score” that can predict the recurrence of breast cancer.

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What's up in AI for Radiology - February 2022

2 March 2022 by Kicky van Leeuwen

Top online courses AI+healthcare | Future Processing becomes Graylight Imaging | business case of AI | welcoming Vara | and more

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Learn about AI in healthcare with these online courses

17 Feb. 2022 by Kicky van Leeuwen

Barely anyone working in the field of AI in healthcare received a formal education on the combination of topics. Simply, because with emerging fields, there usually isn’t much formal education yet. However, by now, with the market maturing, more and more educational resources are becoming available for AI in healthcare specifically. Are you looking to bridge that gap between healthcare and AI? This is the place to start!

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What's up in AI for Radiology - January 2022

8 Feb. 2022 by Kicky van Leeuwen

MaxQ quits Accipio | Aidence and Quantib acquired | 5x FDA | 10x validation studies | AI act summarised | welcoming Circle NVI and XVision | and more

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What's up in AI for Radiology - December 2021

17 Dec. 2021 by Kicky van Leeuwen

Recap 2021 | top searches | best read articles | and happy holidays!

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Can you predict who will develop severe COVID-19 from a chest CT scan?

16 Dec. 2021 by Bram van Ginneken, Alexander Lemm, Luuk Boulogne and Anne Mickan

Last week, we opened STOIC2021: A COVID-19 AI challenge with 10,000 CT scans. Together with its participants, we aim to find the best solution for predicting who will develop severe COVID-19 from a chest CT scan. We will make the final solution easily accessible for everyone. In total, $20,000 in AWS Credits will be awarded to the winning teams.

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What's up in AI for Radiology - November 2021

30 Nov. 2021 by Kicky van Leeuwen

From double to single read+AI | Market overview in 8 minutes | Good Machine Learning Practice | welcoming DeepTrace and Qubiotech | and more

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What's up in AI for Radiology - October 2021

27 Oct. 2021 by Kicky van Leeuwen

What is AI worth? | Two type AI vendors: developers and delivers | Introducing ChestView by GLEAMER | welcoming AIRAmed | and more

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Is AI worth its money?

5 Oct. 2021 by Kicky van Leeuwen

In the application of AI in healthcare, there is still a major question to be answered: who is going to pay - and how much - for AI in healthcare? A health technology assessment may help to find out. We applied this method to assess AI for stroke. In this blog, we discuss the results and implications and make the model available for your own use.

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What's up in AI for Radiology - September 2021

28 Sept. 2021 by Kicky van Leeuwen

Season of collaborations | first blog | dementia AI compared | welcoming Motilent, Medis Medical Imaging, and AI4MedImaging | and more AI for Radiology news

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The origin story of AI for Radiology and a market summary

14 Sept. 2021 by Kicky van Leeuwen

The market of artificial intelligence (AI) software for radiology keeps growing which makes it difficult for pretty much anyone in the field to maintain oversight. That's where AI for Radiology comes in. Read more about what we aim to do, how we do it, and learn what products are on the market today.

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What's up in AI for Radiology - August 2021

7 Sept. 2021 by Kicky van Leeuwen

Reimbursement for AI | head-to-head TB study | Qure.ai launches qCT-Lung | welcoming SenseTime, Smart Soft Healthcare, AlgoMedica, and annalise.ai | and more AI for Radiology news

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What's up in AI for Radiology - June 2021

7 Sept. 2021 by Kicky van Leeuwen

How to create impact with AI | mdbrain detects brain aneurysms | Improved breast cancer detection | Welcoming Lucida Medical, BrainScan and MaxQ | and more in this newsletter!

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What's up in AI for Radiology - May 2021

7 Sept. 2021 by Kicky van Leeuwen

Impact of MDR | Avicenna.ai, NICO.LAB and Arterys launch new features | Videos to 'unbox' AI | Welcoming Deep01 Limited | and more

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What's up in AI for Radiology - April 2021

7 Sept. 2021 by Kicky van Leeuwen

Limited evidence of AI products | CE marks for Ultromics, NICO.LAB, and Quantib | WHO advises AI for tuberculosis screening | and more!

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What's up in AI for Radiology - March 2021

7 Sept. 2021 by Kicky van Leeuwen

Arterys launches Neuro AI | Quibim and Imbio receive FDA clearance | icometrix' portfolio expands | The MDR explained | AI: To buy or not to buy

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AI challenges, data, and algorithms

4 March 2021 by Bram van Ginneken

Presentation by Bram van Ginneken held during the European Congress of Radiology 2021 on the how and why of challenges in medical image analysis.

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Why Challenges?

14 Feb. 2021 by Keelin Murphy and Bram van Ginneken

This is an updated version of blog post made years ago when we launched our platform grand-challenge.org. It makes the case for challenges and provides some advice for those interested in setting up their own challenge.

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How to build a global, scalable, low-latency, and secure machine learning medical imaging analysis platform on AWS

24 Aug. 2020 by Razvan Ionasec, Bram van Ginneken and James Meakin

It is hard to imagine the future for medical imaging without machine learning (ML) as its central innovation engine. Countless researchers, developers, start-ups, and larger enterprises are engaged in building, training, and deploying machine learning solutions for medical imaging that are posed to transform today’s medical workflows and the future value of imaging in diagnosis and treatment.

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