Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Wednesday, April 3, 2024

AI Can Assist With Brain Lesion Localisation Following Stroke

 Once we know the EXACT LOCATION; our researchers can determine the EXACT RECOVERY PROTOCOLS that fix such damage. And we can forever remove the stupid saying; 'All strokes are different, all stroke recoveries are different'.

AI Can Assist With Brain Lesion Localisation Following Stroke

Artificial intelligence (AI) may serve as a future tool for neurologists to locate where in the brain a stroke has occurred, according to a study published in Neurology Clinical Practice.

For the study, a large language model, generative pre-trained transformer 4 (GPT-4), was trained on history and neurologic physical examination from published cases

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of acute stroke followed by questions for clinical reasoning.

“Not everyone with stroke has access to brain scans or neurologists, so we wanted to determine whether GPT-4 could accurately locate brain lesions after stroke based on a person’s health history and a neurologic exam,” said Jung-Hyun Lee, MD, State University of New York Downstate Health Sciences University, Brooklyn, New York.

To evaluate the efficacy of GPT-4 for locating lesions in the brain, Dr. Lee and colleagues used 46 published cases of patients with stroke. The researchers fed raw text from patients’ health histories and neurologic exams into GPT-4. They asked the AI to answer 3 questions: whether a patient had 1 or more lesions; on which side of the brain lesions were located; and in which region of the brain the lesions were found. They repeated these questions for each patient 3 times. Results from GPT-4 were then compared with brain scans for each patient.

Researchers found that GPT-4 processed the text from the health histories and neurologic exams to locate lesions in many patients’ brains, identifying which side of the brain the lesion was on, as well as the specific brain region, with the exception of lesions in the cerebellum and spinal cord.

GPT-4 was able to identify the side of the brain where lesions were found with a sensitivity of 74% and a specificity of 87%. It also identified the brain region with a sensitivity of 85% and a specificity of 94%.

When looking at how often the 3 tests had the same result for each patient, GPT-4 was consistent for 76% of patients regarding the number of brain lesions. It was consistent for 83% of patients for the side of the brain, and for 87% of patients regarding the brain regions.

However, when combining its responses to all 3 questions across all 3 times, GPT-4 provided accurate answers for only 41% of patients.

“While not yet ready for use in the clinic, large language models such as generative pre-trained transformers have the potential not only to assist in locating lesions after stroke, they may also reduce healthcare disparities because they can function across different languages,” concluded Dr. Lee. “The potential for use is encouraging, especially due to the great need for improved healthcare in underserved areas across multiple countries where access to neurologic care is limited.”

Reference: https://www.neurology.org/doi/10.1212/CPJ.0000000000200293

SOURCE: American Academy of Neurology

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