The human brain holds many clues about a person's long-term health--in fact, research shows that a person's brain age is a more useful and accurate predictor of health risks and future disease than their birthdate. Now, a new artificial intelligence (AI) model that analyzes magnetic resonance imaging (MRI) brain scans developed by USC researchers could be used to accurately capture cognitive decline linked to neurodegenerative diseases like Alzheimer's much earlier than previous methods. Brain aging is considered a reliable biomarker for neurodegenerative disease risk. Such risk increases when a person's brain exhibits features that appear "older" than expected for someone of that person's age. By tapping into the deep learning capability of the team's novel AI model to analyze the scans, the researchers can detect subtle brain anatomy markers that are otherwise very difficult to detect and that correlate with cognitive decline.

Characters in books are about four times more likely to be male than female, a new study of gender bias in literature has revealed. Researchers at the USC Viterbi School of Engineering used artificial intelligence to examine more than 3,000 English-language books ranging from science fiction and adventure, to mystery and romance - across short stories, poetry and novels. The team found male characters appeared four times as often as females across the books, although that reduced when the author of the work was female. There were also more negative terms used in connection with the female characters such as'weak' and'stupid' compared to'strong' and'power' used for men. 'Gender bias is real, and when we see females four times less in literature, it has a subliminal impact on people consuming the culture,' said author Mayank Kejriwal.

AI has, for some time, been applied to diagnose medical conditions in specific fields. It can build on knowledge of particular disciplines to hone in on details such as the shape of a tumor that suggests breast cancer or abnormal cells that indicate cervical cancer. While AI is very good when trained on years of human data in specific domains, it has not been able to deal with the huge number of diagnostic tests (about 5000) and disorders (about 14,000) of modern clinical practice. Now, a new algorithm developed by engineers at the USC Viterbi School of Engineering can think and learn just like a doctor but with essentially infinite experience. The work comes out of the lab of Gerald Loeb, a professor of biomedical engineering, pharmacy and neurology at USC Viterbi School of Engineering and a trained physician. Loeb spent years applying AI algorithms to haptics and building robots to sense and identify materials and objects.

With a new three-year NSF grant, Ming Hsieh Department of Electrical and Computer Engineering researchers hope to solve the problem of scalable parallelism for AI. Co-PI's Professor Viktor Prasanna, Charles Lee Powell Chair in Electrical and Computer Engineering and Professor Xuehai Qian both from USC Viterbi, along with USC Viterbi alum and assistant professor at Northeastern University Yanzhi Wang, and USC Viterbi senior research associate Ajitesh Srivastava were awarded the $800,000 grant last month. Parallelism is the ability of an algorithm to perform several computations at the same time, rather than sequentially. For artificial intelligence challenges which require fast solutions, like the image processing related to autonomous vehicles, parallelism is an essential step to make these technologies practical to every-day life. Parallelism in neural networks has been explored, but the problem has been scaling it up to a point where it's applicable in time-critical/realtime tasks.

According to the CDC, the suicide rate for individuals 10-24 years old has increased 56% between 2007 and 2017. In comparison to the general population, more than half of people experiencing homelessness have had thoughts of suicide or have attempted suicide, the National Health Care for the Homeless Council reported. Phebe Vayanos, assistant professor of Industrial and Systems Engineering and Computer Science at the USC Viterbi School of Engineering has been enlisting the help of a powerful ally -artificial intelligence- to help mitigate the risk of suicide. In this research, we wanted to find ways to mitigate suicidal ideation and death among youth. Our idea was to leverage real-life social network information to build a support network of strategically positioned individuals that can'watch-out' for their friends and refer them to help as needed." Vayanos, an associate director at USC's Center for Artificial Intelligence in Society (CAIS), and her team have been working over the last couple of years to design an algorithm capable of identifying who in a given real-life social group would be the best persons to be trained as "gatekeepers" capable of identifying warning signs of suicide and how to respond. Vayanos and Ph.D. candidate Aida Rahmattalabi, the lead author of the study "Exploring Algorithmic Fairness in Robust Graph Covering Problems," investigated the potential of social connections such as friends, relatives, and acquaintances to help mitigate the risk of suicide. Their paper will be presented at the Thirty-third Conference on Neural Information Processing Systems (NeurIPS) this week. "We want to ensure that a maximum number of people are being watched out for, taking into account resource limitations and uncertainties of open world deployment.

Yolanda Gil, a research director at the USC Viterbi Information Sciences Institute (ISI), co-authored a new 20-year Artificial Intelligence Roadmap. An outbreak of a highly contagious mosquito-borne virus in the U.S. has spread quickly to major cities around the world. It's all hands on deck to stop the disease from spreading–and that includes the deployment of artificial intelligence (AI) systems, which scour online news and social media for relevant data and patterns. In consultation with human scientists, AI systems could help contain infectious diseases and identify effective vaccines. Working with these results, and data gathered from numerous hospitals around the world, scientists discover an interesting link to a rare neurological condition and a treatment is developed.

USC Viterbi Professors Burcin Becerik-Gerber and Gale Lucas launch CENTIENTS, a center aimed at fostering research and collaboration toward human-centered design and integration of intelligent technologies into built environments. In the 1960s cartoon The Jetsons, the future was a world full of self-driving cars and sassy, meticulous robots. Individuals, like the patriarch George, could move through space--and the shower--without having to lift a finger. The mechanisms around him played a pivotal role in making decisions on his behalf, based on a learned understanding of his most basic preferences. For a while, this future seemed distant, but upon us now is an unprecedented opportunity to merge human behavior and preferences with automation to create a personalized, dynamic and improved daily reality for individuals at work and at home.

Neuroscientist Paul Thompson (left) with computer scientist Greg Ver Steeg. Nearly 50 million people worldwide have Alzheimer's disease or another form of dementia. While age is the greatest risk factor for developing the disease, researchers believe most Alzheimer's cases occur as a result of complex interactions among genes and other factors. But those factors and the role they play are not known--yet. In a new study, USC researchers used machine learning to identify potential blood-based markers of Alzheimer's disease that could help with earlier diagnosis and lead to non-invasive ways of tracking the progress of the disease in patients.

Americans spend about 104 hours per year in traffic. Americans spend an average of 25.4 minutes commuting to work, according to U.S. Census Bureau data. For those who are counting, that amounts to 104 hours per year spent in traffic, with averages steadily rising every year. In Southern California, commutes are double the national average and considered the most stressful in the nation. The number of cars on highways increases annually, leading to more intense bottlenecks at interchanges, slower speeds on packed roads, and a higher frequency of accidents. Engineers at USC Viterbi are hoping to reverse that trend by adding a new type of artificial intelligence to traffic speed forecasting technology, giving drivers adaptive and predictive information for the fastest commute in every probable way.

The USC Center for Artificial Intelligence in Society (CAIS)--a joint venture of the USC Suzanne Dworak-Peck School of Social Work and USC Viterbi School of Engineering--will host its first Visiting Fellows Program this summer focused on employing AI to help solve complex societal problems. As part of the Fellows Program, visiting researchers from all over the world will come to USC this summer for up to three months to learn from a working model established by the Center's co-founders, Eric Rice of the USC Suzanne Dworak-Peck School of Social Work and Milind Tambe of the USC Viterbi School of Engineering. The two had successfully collaborated by employing AI to ensure that homeless youth shared important public health information among peers in the youths' own social networks. "Using artificial intelligence to promote the greater good is an emerging area of study with huge potential," said Eric Rice, co-director of CAIS and associate professor at the USC Suzanne Dworak-Peck School of Social Work. "Our goal in establishing this fellowship is to bring together the best and brightest scholars in artificial intelligence and social work to explore breakthrough solutions to age-old problems plaguing many of our cities and communities." Topics to be studied by fellows this summer include suicide prevention among college students; social support for North Korean refugees to help their integration into South Korean society; wildlife conservation through poaching prevention in developing nations' national parks; HIV and substance abuse prevention for homeless youth; and predicting and reducing gang violence in Los Angeles.