Abstract: Electromagnetic computational imaging (ECI) offers a promising solution to electromagnetic inverse scattering problems (ISPs). Whereas it is challenged by its ill-posed nature and ...
Learn more about eLife assessments Blood flow to the brain is a sensitive marker of neuronal activity as well as of a number of diseases, including stroke, tumours and neurodegenerative conditions.
Background Fermented foods are a promising yet underexplored intervention for influencing brain function and mental health through the gut–brain axis. Objective The objective of this study was to ...
Researchers at UC Berkeley and UCSF have developed a new AI foundation model that could help physicians in radiology, or the practice of recognizing and diagnosing medical conditions. The model, named ...
The vision language model, named Pillar, analyzes CT and MRI images with an average AUC of .87 across 350+ findings, 10% - 17% more accurate than the leading publicly available AI models BERKELEY, ...
The vision language model, named Pillar, analyzes CT and MRI images with an average AUC of .87 across 350+ findings, 10% - 17% more accurate than the leading publicly available AI models University of ...
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
Lumexa Imaging, formerly known as US Radiology Specialists, has filed with the SEC to go public and is set to raise as much as $200 million, according to an analysis by Renaissance Capital. The ...
With so much money flooding into AI startups, it’s a good time to be an AI researcher with an idea to test out. And if the idea is novel enough, it might be easier to get the resources you need as an ...
Phase Ib Study of BI 836880 (VEGF/Ang2 nanobody) in Combination With Ezabenlimab (anti–PD-1 antibody) in Patients With Advanced or Metastatic Solid Tumors Accurately identifying patients who will ...
Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...
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