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Dr. Kira Radinsky: "We try to identify with the help of medical files when to make a pro-active appointment"

https://m.calcalist.co.il/Article.aspx?guid=sjpcruuhs&utm_source=m.calcalist.co.il&utm_medium=Share&utm_term=sjpcruuhs&utm_campaign=whatsapp [caption id="attachment_3183" align="aligncenter" width="300"] Dr. Kira Radinsky[/caption]  

Prof. Yaniv Romano from the Faculty of Electrical and Computer Engineering and his colleagues at MIT on the limits of uncertainty https://infovalue.online/placing-clear-bounds-on-uncertainty-mit-information/ [caption id="attachment_3064" align="aligncenter" width="200"] Prof. Yaniv Romano of the Faculty of Electrical and Computer Engineering, Technion[/caption]

Technion-Israel Institute of Technology and Pfizer, one of the world’s premier biopharmaceutical companies, recently signed a collaboration framework agreement to identify opportunities to collaborate and bring forward scientific breakthroughs at the interface between artificial intelligence and drug development. The framework agreement was finalized during the visit of a delegation from Pfizer to the Technion. The delegation was led by Pfizer Chairman and CEO, Dr. Albert Bourla, and included Dr. Mikael Dolsten, Chief Scientific Officer and President, Worldwide Research, Development and Medical; Lidia Fonseca, Executive Vice President and Chief Digital and Technology Officer; and other senior executives. Pfizer leaders met with the Technion President Professor Uri Sivan, members of the Technion’s senior management and Technion faculty members from the fields of life sciences and engineering. Pfizer, a biopharmaceutical company with 170 years of experience developing innovative medicines and vaccines, has made an enormous impact on global health in recent years through its development, with BioNTech, of vaccines that help protect against the COVID-19 virus. In addition to its internal drug discovery efforts, Pfizer regularly collaborates with the biotech industry and academia to identify research and technologies that could lead to scientific breakthroughs. The framework agreement with the Technion is consistent with the Institute’s ambition to advance technological and medical developments.

The Pfizer delegation led by Pfizer Chairman and CEO, Dr. Albert Bourla with the Technion delegation led by Technion President Professor Uri Sivan

“Human health is one of the grand challenges facing humanity in the 21st century,” said Technion President Prof. Uri Sivan. “Like other global challenges, today’s scientific and technological breakthroughs require multidisciplinary research and close cooperation between academia and industry. We recently launched Tech.AI, Technion’s Artificial Intelligence Hub, to serve as the main Technion platform providing faculty & students from all Technion units with the best possible access to the forefront of AI research and application. Cooperation with industry, where the great challenges lie, is vital to an undertaking of this kind, and I am therefore looking forward to Pfizer’s potential contributions to this mission.” During their visit, the guests met leading Technion researchers working in the field of AI in the context of human health: Associate Professor Shai Shen-Orr from the Rappaport Faculty of Medicine; Professor Tomer Shlomi from the Henry and Marilyn Taub Faculty of Computer Science; Assistant Professor Dvir Aran from the Faculty of Biology and the Taub Faculty of Computer Science; Assistant Professor Noga Ron-Harel from the Faculty of Biology; and Assistant Professor Uri Shalit from the Faculty of Data and Decision Sciences. According to Prof. Shai Shen-Orr, “the Technion is a leading institution in the field of AI, ranked first in Europe in this field by CS ranking. Our Tech.AI center brings together the Technion’s activity in this field. We are extremely thrilled with the agreement with Pfizer, which will offer Technion researchers close encounters with real-world challenges in drug development, help identify potential applications of AI to drug research and development and expand the Technion’s capabilities in translational research.”

Tech.AI to Launch a new series of talks in collaboration with Matam Hi Tech Park to bring the forefront of Technion AI research to High Tech companies engineers

What do you do on Mondays at 4pm? Starting in January 16.1 2023, Tech.AI, the Center for Artificial Intelligence at the Technion, will hold a series of weekly lectures by the best Technion researchers and members At Tech.AI, in the new TECH & TALK complex in Matam. The activity takes place as part of a collaboration between the Technion and Matam Park. We invite you to register for the "Tech.AI on stage" series, which will allow you to get to know and learn directly from the front of the Technion's work, to create and strengthen collaborations with the Technion's researchers, and to establish the park community with us. Image Denoising - Not What You Think! Prof. Michael Elad, Faculty of Computer Science. Image denoising – removal of white additive Gaussian noise from an image – is one of the oldest and most studied problems in image processing. An extensive work over several decades has led to thousands of papers on this subject, and to many well-performing algorithms for this task. As expected, the era of deep learning has brought yet another revolution to this subfield, and took the lead in today’s ability for noise suppression in images. All this progress has led some researchers to believe that “denoising is dead”, in the sense that all that can be achieved is already done. Exciting as all this story might be, this talk IS NOT ABOUT IT! Our story focuses on recently discovered abilities and vulnerabilities of image denoisers. In a nut-shell, we expose the possibility of using image denoisers for serving other problems, such as regularizing general inverse problems and serving as the engine for image synthesis. We also unveil the (strange?) idea that denoising (and other inverse problems) might not have a unique solution, as common algorithms would have you believe. Instead, we will describe constructive ways to produce randomized and diverse high perceptual quality results for inverse problems. Speaker’s Bio: Michael Elad holds a B.Sc. (1986), M.Sc. (1988) and D.Sc. (1997) in Electrical Engineering from the Technion in Israel. Since 2003 he holds a faculty position in the Computer-Science department at the Technion. Prof. Elad works in the field of signal and image processing, specializing in particular on inverse problems, sparse representations and deep learning. He has authored hundreds of publications in leading venues, many of which have led to exceptional impact. Prof. Elad has served as an Associate Editor for IEEE-TIP, IEEE-TIT, ACHA, SIAM-Imaging-Sciences – SIIMS and IEEE-SPL. During the years 2016-2021 Prof. Elad served as the Editor-in-Chief for SIIMS. Michael received numerous teaching and research awards and grants, including an ERC advanced grant in 2013, the 2008 and 2015 Henri Taub Prizes for academic excellence, and the 2010 Hershel-Rich prize for innovation, the 2018 IEEE SPS Technical Achievement Award for contributions to sparsity-based signal processing; the 2018 IEEE SPS Sustained Impact Paper Award for his K-SVD paper, and the 2018 SPS best paper award for his paper on the Analysis K-SVD. Michael is an IEEE Fellow since 2012, and a SIAM Fellow since 2018.  

Sleep staging is an essential component in the diagnosis of sleep disorders and the management of sleep health. Researchers from the Laboratory for Artificial Intelligence in Medicine, headed by Dr. Joachim Behar showed that it is possible to accurately measure sleep stages using photoplethysmography (PPG) signals recorded with standard oximetry. This opens the door for the development of wearable devices that can be used to diagnose sleep disorders and improve sleep health. The study, which analyzed 23,055 hours of continuous nocturnal data, demonstrates the feasibility of using the PPG signal to robustly perform sleep staging, which is traditionally a labor-intensive process. The research was published in IEEE Journal of Biomedical and Health Informatics (JBHI). The authors of the paper are Kevin Kotzen, Dr. Peter Charlton, Sharon SALABI, Léa Amar, Prof. Amir Landesberg, and Dr. Joachim Behar. Read the full paper: https://lnkd.in/dSiquJjq.  

Another technological breakthrough at the Technion! Ready to break new ground? Take a look at what Professor Shahar Kvatinsky from the Andrew and Erna Viterby Faculty of Electrical & Computer Engineering has been up to with his team. Using a new type of computer architecture that combines both processing and storage in the same hardware, Professor Kvatinsky and his team have designed a neuromorphic computer chip and taught it to recognize handwriting using deep-belief algorithms. The chip is based on commercial technology from Tower Semiconductor and has achieved 97% accuracy in recognition while consuming minimal energy. Used in AI and machine-learning applications, the goal of neuromorphic hardware is to create more powerful and efficient computers that can learn and adapt to new situations. Together with Tower Semiconductor, the study was led by two researchers in Prof. Kvatinsky’s lab: postdoctoral fellow Dr. Wei Wang and Phd student Loai Danial. The work was also supported by the European Research Council (ERC) and the EU Horizon 2020 Future and Emerging Technologies (FET)-OPEN program. Professor Shahar Kvatinsky  

Dr. AI, What’s My Diagnosis? A Technion-developed deep-learning system looks at breast cancer scans better than a human ever could.
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An Israeli scientist collaborating with British researchers has welcomed the “fantastic opportunity” of a UK-Israel deal which could be on the cards as Britain scrambles to replace the EU with other science power houses after it was booted out of the bloc’s flagship innovation programme.
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This is already a well-known anecdote: it took the Moderna company two days to develop the corona vaccine from the moment it had the RNA sequence of the virus. But what was more complex, it turns out, was finding how to introduce the vaccine into the body.
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