Watch now: Bloomington police discuss Jelani Day remains identified Kourtney Kardashian and Megan Fox team up for sexy SKIMS campaign Watch now: Jelani Day's mother calls on local police for answers Watch now: Mother of missing ISU graduate student Jelani Day pleads for her son's return Watch now: Pritzker speaks about Illinois electric vehicle expansion Watch now: ISU president talks about graduate worker negotiations Watch now: Bloomington police discuss impact of Jelani Day case Watch now: Jelani Day's mother speaks about her missing son Watch now: Bloomington Police discuss Jelani Day identification Can the Philadelphia Phillies make the playoffs? Watch now: Coroner confirms remains found in Illinois river are Jelani Day's Watch now: Autumnal Equinox marks beginning of fall Watch now: Andy Dalton's fate hanging in balance with his knee Watch now: Durbin says push for immigration reform isn't over Watch now: Conor McGregor mocked for first pitch at Cubs game Watch now: Jelani Day's mother calls on local police for answers Watch now: Jelani Day's mother speaks about her missing son Can the Philadelphia Phillies make the playoffs? Watch now: Coroner confirms remains found in Illinois river are Jelani Day's Watch now: Durbin says push for immigration reform isn't over

According to a new study in the journal Radiology, AI-driven deep learning may be better at distinguishing between the mammograms of women who will later develop breast cancer and those who will not.

Now, Penn State researchers have used artificial intelligence (AI) to clear up that noise, drastically facilitating and improving near real-time observation of volcanic movements and the detection of volcanic activity and unrest. "The shape of volcanoes is constantly changing and much of that change is due to underground magma movements in the magma plumbing system made of magma reservoirs and conduits," said Christelle Wauthier, associate professor of geosciences and Institute for Data and Computational Sciences (ICDS) faculty fellow. "Much of this movement is subtle and cannot be picked up by the naked eye." Geoscientists have used several methods to measure the ground changes around volcanoes and other areas of seismic activity, but all have limitations, said Jian Sun, lead author of the paper and a postdoctoral scholar in geosciences, funded by Dean's Postdoc-Facilitated Innovation through Collaboration Award from the College of Earth and Mineral Sciences. He added that, for example, scientists can use ground stations, such as GPS or tiltmeters, to monitor possible ground movement due to volcanic activity.

RADAR satellites can collect massive amounts of remote sensing data that can detect ground movements--surface defomations--at volcanoes in near real time. These ground movements could signal impending volcanic activity and unrest; however, clouds and other atmospheric and instrumental disturbances can introduce significant errors in those ground movement measurements. Now, Penn State researchers have used artificial intelligence (AI) to clear up that noise, drastically facilitating and improving near real-time observation of volcanic movements and the detection of volcanic activity and unrest. "The shape of volcanoes is constantly changing and much of that change is due to underground magma movements in the magma plumbing system made of magma reservoirs and conduits," said Christelle Wauthier, associate professor of geosciences and Institute for Data and Computational Sciences (ICDS) faculty fellow. "Much of this movement is subtle and cannot be picked up by the naked eye."

Noam Chomsky is one of the greatest minds of our time and is one of the most cited scholars in history. He is a linguist, philosopher, cognitive scientist, historian, social critic, and political activist. He has spent over 60 years at MIT and recently also joined the University of Arizona. This conversation is part of the Artificial Intelligence podcast. As I explain in the introduction, due to an unfortunate mishap, this conversation is audio-only.

Only 7 percent of patients live five years after diagnosis of pancreatic cancer, the lowest rate for any cancer, according to the American Cancer Society. Elliot K. Fishman, MD, a researcher and radiologist at Johns Hopkins, is on the forefront of trying to change this statistic, and he's using artificial intelligence to do it. Fishman aims to spot pancreatic cancers far sooner than humans alone can by applying GPU-accelerated deep learning artificial intelligence to the task. Johns Hopkins is suited to developing a deep learning system because it has the massive amounts of data on pancreatic cancer needed to teach a computer to detect the disease in a CT scan. Hospital researchers also have NVIDIA's DGX-1 AI Supercomputer.

According to CEO Kaisa Helminen, Fimmic Ltd is a software company that operates in the medical sector. The company provides software solutions that utilize artificial intelligence (AI) and machine vision in tissue section analytics. Fimmic's staff consists of professionals from various fields who have comprehensive knowledge of medicine and software development, as well as solid experience in deep learning AI technologies and life science business. Fimmic's software solutions are originally based on inventions created by the company's Chief Scientific Officer Johan Lundin and his brother, Director of Concept Design, Mikael Lundin. The brothers, who are both medical doctors, originally developed the cloud-based software platform for research use, to speed up the analysis and sharing of extremely large microscope images taken from tissues sections.

Researchers from Purdue University have developed a method using functional magnetic resonance imaging (fMRI) and computer algorithms to map the neural networks of the visual cortex and to build a model of their visual experience as it occurs. As recently reported in Science, the researchers have made possible technology that once belonged in the realm of science fiction. During the "training" phase of the research project, women were shown video clips of people, animals, or scenes from nature. Each video clip was shown multiple times to enable the research team to collect data on the neural activity of the visual cortex of the brain as it responded to aspects of each clip such colour, spatial orientation, or size. Researchers then used this data to make predictions regarding which areas would be stimulated when that same person watched a specific video clip.

Predicting & preventing cyber-attacks: With WannaCry making havoc in many organizations, machine learning algorithms have become extremely important to look for patterns in how the data is accessed, and report anomalies that could predict security breaches. Algorithmic Trading: Today many of financial trading decisions are made using algorithmic trading at higher speed, to make huge profits. Fraud Detection: This is still one of the key issues in all the financial transactions. With the help of deep learning/artificial intelligence, the identification and prediction of frauds have become more accurate. Recommendation Engines: In this digital age, every business is trying hyper-personalization using recommendation engines to give you a right offer at right time.