麻豆传媒

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A powerful new software platform called the Playbook Workflow Builder is set to transform biomedical research by allowing scientists to conduct complex and customized data analyses without advanced programming skills. An article that describes the new platform was published in the April 3 online issue of the journal PLOS Computational Biology. Developed by a multi-institutional team that was led by Icahn School of Medicine at Mount Sinai investigators as part of the National Institutes of Health Common Fund Data Ecosystem (CFDE) program, researchers from across the United States developed the web-based platform that enables scientists to analyze and visualize their own data independently through an intuitive, interactive interface.

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The Icahn School of Medicine at Mount Sinai has launched the AI Small Molecule Drug Discovery Center, a bold endeavor that harnesses artificial intelligence (AI) to revolutionize drug development. The new Center will integrate AI with traditional drug discovery methods to identify and design new small-molecule therapeutics with unprecedented speed and precision. Unlike conventional drug discovery, which can take years and cost billions, AI-driven approaches enable researchers to rapidly navigate a vast chemical landscape, including natural products, to pinpoint promising drug candidates. By leveraging Mount Sinai鈥檚 world-leading expertise in machine learning, chemical biology, and biomedical data science, the Center aims to bring innovative treatments to patients faster鈥攑articularly for diseases with urgent unmet needs, including cancer, metabolic disorders, and neurodegenerative diseases.

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Brian Brown, PhD, Director of the Icahn Genomics Institute at the Icahn School of Medicine at Mount Sinai, has been elected to the College of Fellows of the American Institute for Medical and Biological Engineering (AIMBE).

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Study led by Mount Sinai researcher could lead to more widespread use of imaging technique to improve survival and prevent complications

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Trial led by Mount Sinai researcher could save lives for patients in need of urgent surgery, invasive procedures, or experiencing major bleeding

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New Center Aims to Accelerate AI Research and Personalized Treatment in Children鈥檚 Health

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Researchers at the Icahn School of Medicine have developed a powerful AI tool, built on the same transformer architecture used by large language models like ChatGPT, to process an entire night鈥檚 sleep. To date, it is one of the largest studies, analyzing 1,011,192 hours of sleep. Details on their findings were reported in the March 13 online issue of the journal Sleep [https://doi.org/10.1093/sleep/zsaf061]. The model, called patch foundational transformer for sleep (PFTSleep), analyzes brain waves, muscle activity, heart rate, and breathing patterns to classify sleep stages more effectively than traditional methods, streamlining sleep analysis, reducing variability, and supporting future clinical tools to detect sleep disorders and other health risks.

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Resilience program born during the height of COVID-19 to address mental health needs of Mount Sinai鈥檚 workforce expands to the general public

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Case marks the beginning of a multi-site pivotal trial to evaluate Abbott鈥檚 system for management of treatment-resistant depression

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Findings could improve long-term outcomes for patients