A new study from Insilico Medicine is harnessing artificial intelligence to unravel the complex links between aging and idiopathic pulmonary fibrosis (IPF), a progressive lung disease predominantly impacting the elderly.

Researchers from the United Arab Emirates, U.S. and China have developed AI-driven tools that not only deepen understanding of the disease’s underlying mechanisms but may also pave the way for more targeted therapies and improved management options for patients.

The results , which were published in Aging this summer, revealed significant findings regarding the intersection of aging, biology and IPF progression.

The study presented two deep learning models: a proteomic aging clock developed with UK Biobank data and an abridged version of P3GPT, a transformer-bas

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