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AI identifies tumor aging patterns to predict immunotherapy response across multiple cancer types

Even when given the same drug, some patients respond well while others show little or no response. This is particularly true of immunotherapy. A research team at POSTECH (Pohang University of Science and Technology) has developed an artificial intelligence (AI) technology that can predict, in advance, which patients are likely to benefit from treatment.

A research team led by professor Sanguk Kim of the Department of Life Sciences and the Graduate School of Convergence Science and Technology at POSTECH, together with Minsoo Kim, an integrated MS-Ph. D. student at the Graduate School of Artificial Intelligence, has developed a machine-learning method that analyzes genetic information from cancer patients to predict their response to immunotherapy. The study was recently published in npj Digital Medicine.

Cellular senescence in pediatric anthracycline-induced cardiomyopathy

Address correspondence to: James Martin, Baylor College of Medicine, One Baylor Plaza, Houston, Texas, 77,030, USA. Phone: 713.798.5931; Email: [email protected].

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1Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.

Advanced AI tool estimates biological age and predicts cancer survival from face photos

Researchers are using AI tools to analyze simple facial photographs to determine key indicators of a person’s health. Mass General Brigham researchers built FAHR-Face (Foundation Artificial Intelligence for Health Recognition), a large AI foundation model trained on over 40 million face images.

Rutgers And IBM Demonstrate Real-Time Control Across 100 Qubits

PRESS RELEASE — Researchers from Rutgers, IBM and collaborating institutions have shown that a quantum computer can check what is happening inside it and respond while it is running, repeatedly resetting parts of the system to bring chaotic behavior under control.

The advance is a critical step toward building larger, more reliable quantum computers.

Today’s quantum computers operate according to the unusual rules governing atoms and other extremely small particles. They could one day solve problems beyond the reach of conventional computers — designing better batteries and cleaner industrial catalysts, simulating molecules and materials too complex for today’s computers, and running certain artificial intelligence programs.