1. UNIFYING MIND AND MACHINE THROUGH BRAIN-COMPUTER INTERFACES
Using computers to communicate is not a new idea by any means, but creating direct interfaces between technology and the human mind without the need for keyboards, mice, and monitors is a cutting-edge area of research that has significant applications for some patients.
Neurological diseases and trauma to the nervous system can take away some patients’ abilities to speak, move, and interact meaningfully with people and their environments. Brain-computer interfaces (BCIs) backed by artificial intelligence could restore those fundamental experiences to those who feared them lost forever.
“If I’m in the neurology ICU on a Monday, and I see someone who has suddenly lost the ability to move or to speak, we want to restore that ability to communicate by Tuesday,” said Leigh Hochberg, MD, PhD, Director of the Center for Neurotechnology and Neurorecovery at MGH.
“By using a BCI and artificial intelligence, we can decode the neural activates associated with the intended movement of one’s hand, and we should be able to allow that person to communicate the same way as many people in this room have communicated at least five times over the course of the morning using a ubiquitous communication technology like a tablet computer or phone.”
Brain-computer interfaces could drastically improve quality of life for patients with ALS, strokes, or locked-in syndrome, as well as the 500,000 people worldwide who experience spinal cord injuries every year.
2. DEVELOPING THE NEXT GENERATION OF RADIOLOGY TOOLS
Radiological images obtained by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the inner workings of the human body. But many diagnostic processes still rely on physical tissue samples obtained through biopsies, which carry risks including the potential for infection.
Artificial intelligence will enable the next generation of radiology tools that are accurate and detailed enough to replace the need for tissue samples in some cases, experts predict.
We want to bring together the diagnostic imaging team with the surgeon or interventional radiologist and the pathologist,” said Alexandra Golby, MD, Director of Image-Guided Neurosurgery at Brigham & Women’s Hospital (BWH). “That coming together of different teams and aligning goals is a big challenge.”
“If we want the imaging to give us information that we presently get from tissue samples, then we’re going to have to be able to achieve very close registration so that the ground truth for any given pixel is known.”
Succeeding in this quest may allow clinicians to develop a more accurate understanding of how tumors behave as a whole instead of basing treatment decisions on the properties of a small segment of the malignancy.
Providers may also be able to better define the aggressiveness of cancers and target treatments more appropriately.
Artificial intelligence is helping to enable “virtual biopsies” and advance the innovative field of radiomics, which focuses on harnessing image-based algorithms to characterize the phenotypes and genetic properties of tumors.