FAU Awarded U.S. Air Force Office of Scientific Research Grant to Improve Learning and Operation of AI Systems

Researchers will develop new theory and methods to curate training data sets for artificial intelligence (AI) learning and screen real-time operational data for AI field deployment. They will develop technology to identify faulty, unusual and irregular information for AI learning and operations that rely on data, and will provide critical alerts to troubleshoot a problem before it occurs. This data-quality evaluation technology is being developed for a number of industries ranging from the military to cybersecurity to medical diagnostics.

Read more

AI gets a boost via LLNL, SambaNova collaboration

Lawrence Livermore National Laboratory (LLNL) has installed a state-of-the-art artificial intelligence (AI) accelerator from SambaNova Systems, the National Nuclear Security Administration (NNSA) announced today, allowing researchers to more effectively combine AI and machine learning (ML) with complex scientific workloads.

Read more

Scientists voice concerns, call for transparency and reproducibility in AI research

In an article published in Nature on October 14, 2020, scientists at Princess Margaret Cancer Centre, University of Toronto, Stanford University, Johns Hopkins, Harvard School of Public Health, Massachusetts Institute of Technology, and others, challenge scientific journals to hold computational researchers to higher standards of transparency, and call for their colleagues to share their code, models and computational environments in publications.

Read more

Assessing State of the Art in AI for Brain Disease Treatment

The range of AI technologies available for dealing with brain disease is growing fast, and exciting new methods are being applied to brain problems as computer scientists gain a deeper understanding of the capabilities of advanced algorithms. In APL Bioengineering, Italian researchers conducted a systematic literature review to understand the state of the art in the use of AI for brain disease. Their qualitative review sheds light on the most interesting corners of AI development.

Read more

American College of Radiology and University of Pennsylvania Create Joint Program to Advance Quantitative Imaging Diagnostics and Analytics

The American College of Radiology® (ACR®) Center for Research and Innovation™ (CRI) is pleased to announce a new collaborative effort with the Center for Biomedical Image Computing & Analytics (CBICA) in the Perelman School of Medicine at the University of Pennsylvania (Penn). The collaboration will leverage the ACR’s industry-leading research infrastructure and Penn’s scientific expertise in a joint effort to more rapidly advance imaging informatics.

Read more

The Future of Precision Medicine

Precision medicine is a rapidly growing approach to health care that focuses on finding treatments and interventions that work for people based on their genetic makeup, rather than their symptoms.

Zeeshan Ahmed, director of the new Ahmed Lab at Rutgers Institute for Health, Health Care Policy and Aging Research, discusses the future of precision medicine, what needs to be done to successfully analyze the data necessary to develop individualized treatments and the role genetics play during the COVID-19 pandemic.

Read more