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A UK-based applied science company, focused on supporting cancer diagnostics with machine learning, is bringing its award-winning solution to the United Arab Emirates (UAE).

Kheiron Medical Technologies has partnered with the UAEs Atlas Medical to launch Mia, its breast cancer screening solution that supports radiologists in reducing errors in cancer detection, in the region.

Launched in 2019, Mia which stands for mammography intelligent assessment uses artificial intelligence (AI) to work as a second reader in workflow. Should the radiologist (first human reader) and Mia disagree on a result, then a second radiologist is brought in for a third opinion.

Our mission at Kheiron is to support breast screening professionals in the fight against breast cancer with proven and effective AI-enabled tools, said Alex Hamlow, Kheirons Chief Commercial Officer. Were excited that Mia is the first AI independent reader solution available for use within the breast screening community in the UAE. Based on its performance in the UK and Europe, Mia represents a major breakthrough in helping radiologists dramatically improve breast cancer detection and patient outcomes.

He continued: According to the WHOs International Agency for Research on Cancer, breast cancer was the most prevalent of all cancers detected in the UAE in 2020, accounting for 38.8% of all new cancer cases detected in women. Im excited that Mia can help both radiologists and the women they care for.

WHY IT MATTERS

There are several advantages to using AI technology in cancer screening, says the company.

Using AI technology for the second screening frees up clinicians to spend time with patients, reduces the pressure to find more radiologists, and has the potential to screen greater numbers of women more quickly.

It also prevents unnecessary biopsies.

According to a statement by Kheiron, Mia has learnt to read mammograms to the same level of detail as a consulting radiologist.

ON THE RECORD

I am delighted that Kheiron Medical Technologies is bringing their breakthrough AI platform for breast screening, Mia, to the Gulf region, and that the UKs Department for International Trade played a role in making this happen, said Simon Penney, Her Majestys Trade Commissioner for the Middle East. Kheirons technology brings pioneering AI to the frontline, freeing up clinicians time and helping to save lives.

V. Kalyanasundaram, General Manager for Atlas Medical in Dubai and the Northern Emirates, added: We are looking forward to bringing the Mia solution to the breast screening community throughout the UAE. It has tremendous potential to transform breast screening for radiologists and for women.

By improving radiologist productivity and empowering breast screening professionals to detect potential malignancies more accurately and quickly, Mia ultimately will help save more lives in the fight against breast cancer.

In addition to the UAE, Mia is reportedly set to launch soon in Qatar and Oman, pending local requirements.

More:
British AI solution for breast cancer screening arrives in the UAE - Mobihealth News

Linux Foundation with support from IBM and Call for Code hosts Intelligent Supervision Assistant for Construction project from Build Change to help builders identify structural issues in masonry walls or concrete columns, especially in areas affected by disasters

SAN FRANCISCO, June 10, 2021 The Linux Foundation, the nonprofit organization enabling mass innovation through open source, today announced it will host the Intelligent Supervision Assistant for Construction (ISAC-SIMO) project, which was created by Build Change with a grant from IBM as part of the Call for Code initiative. The Autodesk Foundation, a Build Change funder, also contributed pro-bono expertise to advise the projects development.

Build Change helps save lives in earthquakes and windstorms. Its mission is to prevent housing loss caused by disasters by transforming the systems that regulate, finance, build and improve houses around the world.

ISAC-SIMO packages important construction quality assurance checks into a convenient mobile app. The tool harnesses the power of machine learning and image processing to provide feedback on specific construction elements such as masonry walls and reinforced concrete columns. Users can choose a building element check and upload a photo from the site to receive a quick assessment.

ISAC-SIMO has amazing potential to radically improve construction quality and ensure that homes are built or strengthened to a resilient standard, especially in areas affected by earthquakes, windstorms, and climate change, said Dr. Elizabeth Hausler, Founder & CEO of Build Change. Weve created a foundation from which the open source community can develop and contribute different models to enable this tool to reach its full potential. The Linux Foundation, building on the support of IBM over these past three years, will help us build this community.

ISAC-SIMO was imagined as a solution to gaps in technical knowledge that were apparent in the field. The app ensures that workmanship issues can be more easily identified by anyone with a phone, instead of solely relying on technical staff. It does this by comparing user-uploaded images against trained models to assess whether the work done is broadly acceptable (go) or not (no go) along with a specific score. The project is itself built on open source software, including Python through Django, Jupyter Notebooks, and React Native.

Due to the pandemic, the project deliverables and target audience have evolved. Rather than sharing information and workflows between separate users within the app, the app has pivoted to provide tools for each user to perform their own checks based on their role and location. This has led to a general framework that is well-suited for plugging in models from the open source community, beyond Build Changes original use case, said Daniel Krook, IBM Chief Technology Officer for the Call for Code Global Initiative.

IBM and The Linux Foundation have a rich history of deploying projects that fundamentally make change and progress in society through innovation and remain committed during COVID-19. The winner of the 2018 Call for Code Global Challenge, Project OWL, contributed its IoT device firmware in March 2020 as the ClusterDuck Protocol, and since then, twelve more Call for Code deployment projects like ISAC-SIMO that address disasters, climate change, and racial justice, have been open sourced for communities that need them most.

The project encourages new users to contribute and to deploy the software in new environments around the world. Priorities for short term updates include improvements in user interface, contributions to the image dataset for different construction elements, and support to automatically detect if the perspective of an image is flawed. For more information, please visit: https://www.isac-simo.net/docs/contribute/.

For more information on IBMs role in this work, please visit: https://developer.ibm.com/callforcode/blogs/call-for-code-app-uses-ai-to-make-homes-safer-and-more-resilient/.

About The Linux Foundation

Founded in 2000, The Linux Foundation is supported by more than 1,000 members and is the worlds leading home for collaboration on open source software, open standards, open data, and open hardware. The Linux Foundations projects are critical to the worlds infrastructure including Linux, Kubernetes, Node.js, and more. The Linux Foundations methodology focuses on leveraging best practices and addressing the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.

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The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.

Media Contact

Jennifer Cloerfor the Linux Foundation503-867-2304jennifer@storychangesculture.com

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New Open Source Project Uses Machine Learning to Inform ...

Discovering better theories

Theories of human decision-making have proliferated in recent years. However, these theories are often difficult to distinguish from each other and offer limited improvement in accounting for patterns in decision-making over earlier theories. Peterson et al. leverage machine learning to evaluate classical decision theories, increase their predictive power, and generate new theories of decision-making (see the Perspective by Bhatia and He). This method has implications for theory generation in other domains.

Science, abe2629, this issue p. 1209; see also abi7668, p. 1150

Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this goal can be accelerated by using large datasets to power machine-learning algorithms that are constrained to produce interpretable psychological theories. Conducting the largest experiment on risky choice to date and analyzing the results using gradient-based optimization of differentiable decision theories implemented through artificial neural networks, we were able to recapitulate historical discoveries, establish that there is room to improve on existing theories, and discover a new, more accurate model of human decision-making in a form that preserves the insights from centuries of research.

Original post:
Using large-scale experiments and machine learning to discover theories of human decision-making - Science Magazine

PARIS, June 15, 2021 /PRNewswire/ --ManpowerGroup (NYSE: MAN) joins the biggest names in tech as HR partner of the world-famous Viva Technology (VivaTech) conference held inParis and online this week. ManpowerGroup will share innovation that improves people's lives and solves one of the world's most pressing social issues - how to provide meaningful, sustainable employment for all. The hybrid event will attract more than 8,000 attendees and ManpowerGroup has partnered since its launch five years ago to support start-ups and accelerate tech for good.

"Our innovations are driven by impact - upskilling people at speed and scale and matching people to jobs with better accuracy than either humans or machines could do on their own," said Jonas Prising, ManpowerGroup Chairman & CEO. "We're excited to return to VivaTech to showcase how we'reusing AI, people analytics and human expertise to createa more resilient, future-ready workforce. Building a better, brighter future of work requires bold, disruptive ideas and collaboration across business, government and education this is how we will create sustainable skills, resilient communities, and greater prosperity for all."

ManpowerGroup will host 30 game-changing start-ups and showcase innovation and digital workforce transformation on its #FutureofWork lab including:

ManpowerGroup will host its Talent Center for the fifth year, an online and in-person space where in-demand tech workers can experience coaching, assessment and skills development and match with open positions in the world's leading tech companies.

Human Expertise: On Wednesday June 16ManpowerGroup's Chairman & CEOJonas Prisingwill be joined by Tomas Chamorro-Premuzic, ManpowerGroup's Chief Talent Scientist for Human Age Reconnected a discussion moderated by CNN's Margot Haddad on CEO takeaways from the crisis and AI, bias and ethics in recruitment.

Follow @ManpowerGroup at Viva Tech on Twitter and join the conversation using #sustainableskills #FutureofWork #VivaTech. https://vivatechnology.com/partners/manpower-group

To find out more about ManpowerGroup's Future for Workers insight series read The Skills Revolution Rebooton the impact of COVID-19 on digitization and skills and The Future for Workers, By Workers.

ABOUT MANPOWERGROUPManpowerGroup (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast-changing world of work by sourcing, assessing, developing and managing the talent that enables them to win. We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills. Our expert family of brands Manpower, Experis and Talent Solutions creates substantially more value for candidates and clients across more than 75 countries and territories and has done so for over 70 years. We are recognized consistently for our diversity - as a best place to work for Women, Inclusion, Equality and Disability and in 2021 ManpowerGroup was named one of the World's Most Ethical Companies for the 12th year - all confirming our position as the brand of choice for in-demand talent.

SOURCE ManpowerGroup

http://www.manpowergroup.com

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ManpowerGroup Returns to Viva Technology as HR Partner, Showcasing New AI, Machine-Learning and Data-Driven Predictive Performance Tools - PRNewswire

Discover a better theory

In recent years, the theory of human decision making has skyrocketed. However, these theories are often difficult to distinguish from each other and offer less improvement in explaining decision-making patterns than previous theories.Peterson et al. Leverage machine learning to evaluate classical decision theory, improve predictability, and generate new theories of decision making (see Perspectives by Bhatia and He). This method affects the generation of theory in other areas.

Science, Abe2629, this issue p. 1209abi7668, p. See also. 1150

Predicting and understanding how people make decisions is a long-standing goal in many areas, along with a quantitative model of human decision-making that informs both social science and engineering research. did. Show how large datasets can be used to accelerate progress towards this goal by enhancing machine learning algorithms that are constrained to generate interpretable psychological theories. .. Historical discoveries by conducting the largest experiments on risky choices to date and analyzing the results using gradient-based optimizations of differentiable decision theory implemented via artificial neural networks. A new, more accurate model of human decision-making in the form of summarizing, confirming that there is room for improvement of existing theories, and preserving insights from centuries of research.

Discover the theory of human decision-making using extensive experimentation and machine learning

Source link Discover the theory of human decision-making using extensive experimentation and machine learning

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Discover the theory of human decision-making using extensive experimentation and machine learning - Illinoisnewstoday.com