Technion researchers are putting artificial intelligence to work for real with living solutions ranging from health to robotics. In 2021, Technion AI was ranked No.1 in Europe. AI collaborative initiatives at Technion are multidisciplinary, national and global, engaging industry and inspiring whole new generations of scientists and engineers. Currently, 46 Technion researchers are engaged in core AI research areas with more than 100 researchers in AI-related fields, including health and medicine, autonomous vehicles, smart cities, industrial robotics, cybersecurity, natural language processing, FinTech, and human-machine interaction.
Informing Fauci
WE WERE ABLE TO SEE HOW OUR RESEARCH CAN MAKE A REAL IMPACT ON POLICY MAKING… IN FACT THESE PAPERS HAVE BEEN CITED BY ANTHONY FAUCI IN A WHITE HOUSE BRIEFING.
– Prof. Roy Kishony
In the midst of the pandemic, the research team at the laboratory of Prof. Roy Kishony met the global crisis with a rapid scientific response, offering insights, informed strategies, and vital information across the emergency frontier. This included a 2021 publication in Nature Medicine showing that in communities with high vaccination rates, there is significant decline in infection among the unvaccinated. For every 20 percent vaccinated in the community, there was a reduction of a factor of two in the infection rate of the unvaccinated. This paper was cited by Anthony Fauci at a White House briefing and was used by the director of the CDC to inform the decision to lift the recommendation on wearing masks. “It gives a real feeling of how we can close the gap from data to analysis, to actually making a major impact on policy making, and patient lives,” said Kishony.
AI gets real with antibiotics
THIS IS A MAJOR MILESTONE IN PERSONALIZED MEDICINE ON THE WAY TO AI-BASED ANTIBIOTIC TREATMENTS, WHICH ARE PERSONALLY TAILORED TO THE PATIENT.
– Prof. Roy Kishony
In partnership with Israel’s leading healthcare provider, Maccabi Healthcare Services, the Prof. Roy Kishony’s research team recently began applying an AI predictive algorithm to advise doctors on personalized antibiotic treatment for patients, initially focusing on urinary tract infections (UTI). Maccabi doctors report that the algorithm has led to a drop of around 35% in the need to switch antibiotics following the development of bacterial resistance to the drug prescribed.
AI gets personal
Researchers at the Rappaport Faculty of Medicine have developed an innovative algorithm to compare tumors at different stages of treatment. The tuMap algorithm places different tumors on a uniform scale to provide a benchmark for comparison. The tumors of different patients can thus be compared, as well as tumors of the same patient over the course of the disease. The resolution provided by the algorithm enables prediction of clinical indices with high accuracy, outperforming traditional tools. The researchers tested the algorithm on leukemia tumors. The findings were published in Cell Systems by Assoc. Prof. Shai Shen-Orr, Dr. Yishai Ofran, and Dr. Ayelet Alpert, in collaboration with Rambam Health Care Campus, Shaare Zedek Medical Center, and the University of Texas.