AI to have significant, wide-ranging impact on neurological care continuum

Key takeaways:

• AI has the potential to change the way neurological conditions are prevented, managed and treated.
• AI can be applied to both internal and external issues related to the brain.

ORLANDO, Fla. — From analytics to treatment and surgery, the role of AI is likely to expand in the field of neurology within the next generation, according to speakers at a plenary session at the American Neurological Association annual meeting.

A panel of academics, researchers and clinicians said that AI applications either in development or currently utilized hold the potential to expand the entire neuro care continuum, including:

• Machine learning and deep learning, where a large volume of patient data can be shared, analyzed and synthesized among vast health care networks to support diagnosis, decision-making and treatment plans for the patient and physician. These networks can also analyze patient history and genetic factors to determine the likelihood of developing a neurological condition.
• Natural language processing, in which speech or writing is processed almost instantaneously and fed through wearable or implantable devices for real-time feedback which, in turn, can positively impact management of conditions such as Parkinson’s disease and essential tremor.
• Robotics, such as brain-computer interfaces, which can assist individuals with conditions that affect motor function, as well as fiber-optic probes that can pinpoint trouble areas in the brain during surgery to address Alzheimer’s disease, epilepsy, aneurysms and tumors.
• Implantable devices, which may let patients know that a particular treatment may not be optimal, alert patients to potentially dangerous situations related to a neurological condition or provide electrical stimulation to muscle groups which may lead to improve motor function in conditions such as Parkinson’s.

“We're developing tools that use artificial intelligence to help with diagnosis and treatment selection for people with a wide range of brain diseases, including Alzheimer's and other types of dementia,” Paul Thompson, PhD, a professor at the Keck School of Medicine at the University of Southern California who presented data on AI at the conference, told Healio in an email. “We're excited to help medical experts, patients and caregivers learn more about the strengths and limitations of AI in health care."

Further AI applications may assist with streamlining the process for prescribing drugs, along with personalizing health care through methods such as:

• ChatGPT and other forms of predictive or generative text, which can provide quicker transcription and translation of, as well as access to, clinical notes regardless of speech patterns or dialects;
• automated motion sequencing technology that evaluates the efficacy of medications for conditions such as epilepsy;
• predictive models that analyze outcomes for patients requiring intensive care and predict the impact of comorbidities or other conditions on treatment, surgery and recovery; and
• models that scan for confirmation of insurance and immediate authorization, allowing clinicians to more rapidly and accurately recommend appropriate treatment courses.

“Data science is ready to disruptively change neurology practice,” Brian Litt, MD, Perelman Professor of Neurology, Neurosurgery and Bioengineering at the University of Pennsylvania who presented data on AI applications for implantable devices, told Healio in an email. “Making it happen requires innovative ways to share and analyze data at scale and democratizing access to medical information while protecting data privacy, ownership and patient rights.”

Reference:

Artificial Intelligence poised to transform neurological care from diagnosis to treatment, even prevention. https://myana.org/publications/news/artificial-intelligence-poised-transform-neurological-care-diagnosis-treatment. Published Sept. 15, 2024. Accessed Sept. 15, 2024.