This was one finding of a survey by Well-Beat, an Israeli startup whose patient-engagement platform combines machine learning with behavioral …

Israeli space weather researchers report that they used artificial intelligence (AI) to predict powerful radiation outbreaks up to 96 hours before they occurred. Harmful radiation from these eruptions – also known as solar storms -- can have a significant impact on our lives here on Earth. They produce disturbances in atmospheric layers through which communication and GPS signals pass. That leads to disruption of satellite activity, navigation systems, communications and electric grids. Intense radiation bursts also can result in dangerous and costly spacecraft failures.

As the world grows older, issues surrounding elderly care abound: who's taking care of our elderly relatives, are they doing it well, and how do we keep track of well-being and safety in a sensitive way? Israeli startup Sensi.AI thinks it may have the solution with a smart, AI-powered auditory system that monitors a person's daily routine, environment and well-being, which it claims can provide better caregiver retention and quality-of-care assurance– not only for the elderly, but also for babies, special-needs kids and others. "The idea for it came out of my own personal place, to do with my daughter," says Sensi.AI CEO Romi Gubes. "I understood this whole world of caregiving for the helpless, and how much the element of transparency is lacking in order to prevent future problems." This lack of transparency, she explains, is the result of the often-silent population that requires caregiving and can lead to blind spots in the treatment process that inhibit improvement.

Louise Brown, the world's first "test tube" baby, was born in 1978 through in vitro fertilization (IVF). In IVF, sperm and egg meet outside the body and the best resulting embryo is implanted into the womb in hopes of a healthy pregnancy. "There have been so many advancements in the bioscience aspects of IVF since then, but it lags behind other healthcare verticals big time as far as data science -- and there is a lot of data that is not being used," Eran Eshed, CEO and cofounder of Fairtility, tells ISRAEL21c. "Today, the process of assisted reproductive technology is based on experience and subjective judgment. The outcomes are not very impressive – it takes an average of three IVF cycles per patient to take a baby home," says Eshed.

At the beginning of May, confident that the coronavirus curve was safely flattened, Israel sent its children back to school. Within weeks, more than 200 new Covid-19 cases were diagnosed in Jerusalem alone, linked to a single infected "super spreader" teacher who taught in several schools. As a new school year begins, Israel's capital city is trying various strategies to avoid a repeat of that public-health catastrophe. One solution it will use is a mathematical model that predicts -- with no physical testing or patient contact – who's likely to be infected and with what specific respiratory virus. "The idea is to mathematically model the way infectious diseases move in the community," explains EDAS Healthcare CEO Guy Livne. EDAS stands for Electronic Diagnosis And Surveillance.

Hundreds of drugs have been developed to address Alzheimer's disease, says Dr. Shahar Arzy, director of the computational neuropsychiatry lab at Hadassah Hebrew University Medical Center in Jerusalem. "Do you know how many have been found effective? But if patients could be diagnosed in the preclinical stages of the disease, perhaps some of the new biological medications showing excellent results in other domains of neurology could be effective when applied early enough in the course of Alzheimer's disease. Arzy and his colleagues have developed a computer-based system to ferret out early signs of Alzheimer's. The system, dubbed Clara ("a hint towards'clarity of mind,'" Arzy says), is an artificial intelligence-based chatbot that asks patients questions about themselves and their relationships to people, places and events. Clara then uses machine learning to compare that information to a baseline in order to generate a computer-based test tailored for the specific individual that can diagnose very early Alzheimer's. Arzy's team published research results in the Proceedings of the National Academy of Sciences and in the American Psychological Association's journal Neuropsychology showing the method to be 95 percent accurate. Alzheimer's affects the brain's "orientation system" that dictates how a person relates to the world outside. "It's easy to test memory," Arzy says. "I can give you three words and ask you to retrieve them." For example, a patient might remember both the assassination of US President John F. Kennedy and the election of Barack Obama but be confused about which came first. Or a patient might recognize his or her spouse and doctor, but not be able to distinguish which person is standing closer. Orientation can be measured in a functional MRI. Your brain will light up differently if you see a picture of your own daughter vs. someone else's child or a generic image of a baby. "The overlap between how the self is oriented to the world and the brain mechanisms that are disturbed by Alzheimer's disease is astonishing,"Arzy says. In the preclinical stages of Alzheimer's, the orientation system begins to deteriorate, "but people can still compensate for this by tapping into other resources like memory," Arzy says. "They can write down a note, for example.

Running a background check for a sensitive job in an investment bank, government office or large corporation traditionally takes 10 to 15 days. In today's fast-moving world, where a tweet can change everything in a matter of seconds, that's too long. Shlomo Mirvis had been conducting background checks the old fashioned way for Israeli intelligence firm Kela. Mirvis had to do his work manually. "The world of background checks hardly changed in the last 40 years," he tells ISRAEL21c.

Two years ago, Gal Salomon's mother developed sepsis during a stay in the hospital. "It was a big hospital with a lot of patients and no one saw or understood it was happening," Salomon recalls bitterly. "We lost her after two days." So when Salomon, then a partner at Israeli venture capital firm Pitango, was introduced to Clew Medical, he knew immediately that he had to get involved. Clew develops software that uses artificial intelligence (AI) to predict which patients in a hospital's intensive care unit (ICU) are at the highest risk of imminent deterioration, and it alerts staff so they can intervene early.