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.

Sunday, September 6, 2026

Application of artificial intelligence in prediction and management of stroke rehabilitation

Until 100%recovery research is out there, artificial intelligence isn't going to do much good. Wrong goal: the only goal in stroke is 100% recovery! GET THERE! Predictions and 'management' DO NOTHING FOR RECOVERY! If you are that fucking stupid; you need to be fired!

 Application of artificial intelligence in prediction and management of stroke rehabilitation

Weihua Song1,#, Shuai Si2,#, Yinghui Wang3, Hong Chang1,*, Xiaoying Tang2,* 1. Department of Neurology, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, China 2. School of Medical Technology, Zhengzhou Academy of Intelligent Technology, Beijing Institute of Technology, Beijing, China 3. Luohe Orthopedic Hospital, Luohe, China Corresponding author: Hong Chang (changhong@xwhosp.org); Xiaoying Tang (xiaoying@bit.edu.cn) # Those authors contributed equally to this work

Abstract: 


Artificial intelligence (AI) is being studied across the stroke care pathway, but evidence from acute diagnosis, early prognosis, rehabilitation-outcome prediction, and long-term management is often discussed without clearly separating these clinical tasks. This structured narrative review adds an integrated framework that maps each application to its decision point, relevance to rehabilitation, validation level, and readiness for clinical use. Unlike previous technology-centred reviews, it explicitly separates acute prognostic evidence from rehabilitation-specific evidence and distinguishes technical performance from transportability, clinical impact, and rehabilitation benefit. Acute imaging and prognostic models may provide baseline information for later rehabilitation planning, but their diagnostic or prognostic performance does not establish rehabilitation efficacy. Most rehabilitation models and robotic, virtual-reality, brain-computer interface, wearable, and home-monitoring applications remain supported mainly by internal validation or early exploratory studies. Small or selected datasets, limited external and prospective validation, uncertain workflow effects, and sparse patient-centred outcomes continue to constrain clinical interpretation

No comments:

Post a Comment