A technique to cool the planet, in which particles are added to the atmosphere to reflect sunlight, would not require developing special aircraft but could be achieved using existing large planes, according to a new modelling study led by UCL (University College London) researchers.

Most current AI models rely on high-quality scanned ECG images. But in the real world, doctors don’t always have access to perfect scans. They often rely on paper printouts from ECG machines, which they might photograph with a smartphone to share with colleagues or add to a patient’s records. These photographed images can be tilted, crumpled, or shadowed, making AI analysis much more difficult.

To solve this, Dr. Vadim Gliner, a former Ph.D. student in Prof. Yael Yaniv’s Biomedical Engineering Lab at the Technion, in collaboration with the Schuster Lab in the Henry and Marilyn Taub Faculty of Computer Science, has developed a new AI interpretability tool designed specifically for photographed ECG images. This paper was published in npj-Digital Medicine. Using an advanced mathematical technique (based on the Jacobian matrix), this method offers pixel-level precision, meaning it can highlight even the smallest details within an ECG. Unlike previous models, it doesn’t get distracted by the background and can even explain why certain conditions don’t appear in a given ECG.