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First AI-based tool for predicting genomic subtypes of pancreatic cancer from histology slides


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Paris, France and New York, NY June 10, 2021 - AP-HP Greater Paris University Hospitals, the leading European clinical trial center with the largest amount of healthcare data in France dedicated to research and Owkin, a startup pioneering Federated Learning and AI technologies for medical research and clinical development, announced the recent results of their ongoing strategic collaboration at ASCO 2021. The abstract and poster entitled Identification of pancreatic adenocarcinoma molecular subtypes on histology slides using deep learning models demonstrates the first AI-based
tool for predicting genomic subtypes of pancreatic cancer (PDAC) developed from machine learning applied to histology slides. The tool, a trained and validated AI model, is usable in clinical practice worldwide and opens the possibility of patient molecular stratification in routine care and for clinical ....

New York , United States , Saint Antoine , France General , Julien Calderaro , Robert Debr , Ligue Contre Le , Gilles Wainrib , Thomas Clozel , Gustave Roussy , Talia Lliteras , Jean Pierre Hugot , Nature Communications , Ongoing Fruitful Research Collaboration , Greater Paris University Hospitals , Paris University Hospitals , Federated Learning , Chief Scientific Officer , Beaujon Hospital , Amboise Par , Des Tumeurs , Paris University , Ongoing Fruitful Research , Pancreatic Adenocarcinoma , Medicine Health , Clinical Trials ,

New processes for automated fabrication of fiber and silicone composite structures for soft robotics


Credit: SUTD
Researchers from the Singapore University of Technology and Design (SUTD) have developed novel techniques, known as Automated Fibre Embedding (AFE), to produce complex fibre and silicone composite structures for soft robotics applications. Their work was published in
IEEE Robotics and Automation Letters.
Many soft robot components, including sensors and actuators, utilise embedded continuous fibres within elastomeric substrates to achieve various functionalities. However, manual embedding of continuous fibres in soft substrates is challenging due to the complexities involved in handling precise layering, and retaining of the fibres in the patterned positions which are prone to inconsistencies.
In contrast, the AFE approaches developed by the research team led by Assistant Professor Pablo Valdivia y Alvarado, enabled high precision fabrication of complex layered composites without manual user intervention, thus significantly augmenting the range of fa ....

Pablo Valdiviay Alvarado , Singapore University Of Technology , Singapore University , Automated Fibre Embedding , Assistant Professor Pablo Valdivia , Direct Ink Writing , Chemistry Physics Materials Sciences , Technology Engineering Computer Science , Theory Design , Electrical Engineering Electronics , Research Development , Robotry Artificial Intelligence , சிங்கப்பூர் பல்கலைக்கழகம் ஆஃப் தொழில்நுட்பம் , சிங்கப்பூர் பல்கலைக்கழகம் , நேரடி மை எழுதுதல் , வேதியியல் இயற்பியல் பொருட்கள் அறிவியல் ,

Artificial intelligence predicts brain age from EEG signals recorded during sleep studies


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DARIEN, IL - A study shows that a deep neural network model can accurately predict the brain age of healthy patients based on electroencephalogram data recorded during an overnight sleep study, and EEG-predicted brain age indices display unique characteristics within populations with different diseases.
The study found that the model predicted age with a mean absolute error of only 4.6 years. There was a statistically significant relationship between the Absolute Brain Age Index and: epilepsy and seizure disorders, stroke, elevated markers of sleep-disordered breathing (i.e., apnea-hypopnea index and arousal index), and low sleep efficiency. The study also found that patients with diabetes, depression, severe excessive daytime sleepiness, hypertension, and/or memory and concentration problems showed, on average, an elevated Brain Age Index compared with the healthy population sample. ....

United States , Yoav Nygate , American Academy Of Sleep Medicine , Communications Coordinator Corinne Lederhouse , Neural Network Model For Brain Age Prediction , Bits Association , Research Society , Patient Health Conditions , Absolute Brain Age Index , Brain Age Index , Associated Professional Sleep Societies , American Academy , Sleep Medicine , Sleep Research , Based Deep Neural Network Model , Brain Age Prediction , Coordinator Corinne Lederhouse , Medicine Health , Leep Sleep Disorders , Robotry Artificial Intelligence , ஒன்றுபட்டது மாநிலங்களில் , அமெரிக்கன் கலைக்கழகம் ஆஃப் தூங்கு மருந்து , அதன் சங்கம் , ஆராய்ச்சி சமூகம் , மூளை வாழ்நாள் குறியீட்டு , தொடர்புடையது ப்ரொஃபெஶநல் தூங்கு சமூகங்கள் ,