Deans' stroke musings: The Potential of Artificial Intelligence in Predicting Post-Stroke Rehabilitation Outcomes: Statistical Analysis Considering Rivermead Motor Assessment and Activities of Daily Living Indicators and Selected Demographic Variables

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.

Tuesday, December 24, 2024

The Potential of Artificial Intelligence in Predicting Post-Stroke Rehabilitation Outcomes: Statistical Analysis Considering Rivermead Motor Assessment and Activities of Daily Living Indicators and Selected Demographic Variables

Any type of recovery prediction for stroke is absolutely useless to survivors. DELIVER 100% RECOVERY PROTOCOLS! Which is what survivors want! WHY THE FUCK AREN'T YOU DOING THAT?

Laziness? Incompetence? Or just don't care? NO leadership? NO strategy? Not my job? Not my Problem?

I'd have you all fired.

The Potential of Artificial Intelligence in Predicting Post-Stroke Rehabilitation Outcomes: Statistical Analysis Considering Rivermead Motor Assessment and Activities of Daily Living Indicators and Selected Demographic Variables

December 2024
Applied Sciences 14(24):11806

DOI:10.3390/app142411806

License
CC BY 4.0

Authors:

Małgorzata Kuźnar

Cracow University of Technology

Augustyn Lorenc

Cracow University of Technology

Strokes are currently the third most common cause of death worldwide and the leading cause of disability in people over 50 years of age. The functioning of post-stroke patients depends primarily on well-conducted rehabilitation(But no USEFUL PROTOCOLS EXIST, so stop lying about stroke!), both in stationary conditions and at home. The aim of this study was to evaluate the functional outcomes of patients after ischemic stroke who underwent home rehabilitation. The RMA (Rivermead Motor Assessment) and ADL (activities of daily living) scales were used for evaluation. A total of 20 patients underwent a 4-week home rehabilitation program in Cracow. In the studied group, most patients showed functional improvement after the 4-week rehabilitation period. Predictive models were created (Net1, Net2, Net3) using artificial intelligence algorithms, including regression and classification methods. The analysis results indicate that the best outcomes in predicting the RMA and ADL indicators. For Net2, the prediction accuracy for the ADL indicator was 94.4%, which is significantly higher compared to the other indicators. The RMA1-3 indicators achieved relatively low accuracy rates of 38.9–44.4%. In contrast, for Net3, the RMA1-3 indicators showed high accuracy, achieving 89.1–91.3% correct results. The conclusions of the study suggest that using a combination of the Net2 and Net3 models can contribute to optimizing the rehabilitation process, allowing therapy to be tailored to the individual needs of patients. The research proves that it is possible to predict the effect of rehabilitation by using AI. The implementation of such solutions can increase the effectiveness of post-stroke rehabilitation, particularly through the personalization of therapy and dynamic monitoring of patient progress.