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 20, 2020

Artificial intelligence for decision support in acute stroke — current roles and potential

You missed the whole fucking point of using artificial intelligence! Creating recovery protocols! DAMN IT ALL, DOESN'T ANYONE IN STROKE EVER THINK?

The latest here:

Artificial intelligence for decision support in acute stroke — current roles and potential

 

Abstract

The identification and treatment of patients with stroke is becoming increasingly complex as more treatment options become available and new relationships between disease features and treatment response are continually discovered. Consequently, clinicians must constantly learn new skills (such as clinical evaluations or image interpretation), stay up to date with the literature and incorporate advances into everyday practice. The use of artificial intelligence (AI) to support clinical decision making could reduce inter-rater variation in routine clinical practice and facilitate the extraction of vital information that could improve identification of patients with stroke, prediction of treatment responses and patient outcomes. Such support systems would be ideal for centres that deal with few patients with stroke or for regional hubs, and could assist informed discussions with the patients and their families. Moreover, the use of AI for image processing and interpretation in stroke could provide any clinician with an imaging assessment equivalent to that of an expert. However, any AI-based decision support system should allow for expert clinician interaction to enable identification of errors (for example, in automated image processing). In this Review, we discuss the increasing importance of imaging in stroke management before exploring the potential and pitfalls of AI-assisted treatment decision support in acute stroke.

Key points

  • Imaging-based treatment guidance has been demonstrated as an effective approach in patients with a suspected stroke.

  • Clinical trials in which imaging is not used for patient selection are likely to include many patients with minor stroke or stroke mimics, making treatment effects difficult to detect.

  • Artificial intelligence (AI) and machine learning could provide image interpretation that equals or exceeds that of experts and could collate key features to assist clinicians with treatment decisions.

  • AI could be used to generate estimations of likely patient outcomes, which would not only be useful for assisting treatment decisions but also for informing family discussions. (Oh fuck, you don't want this to occur. Current predictions are based upon a 10% full recovery rate.  Tyranny of low expectations which you don't want to occur.)

  • AI-based decision assistance systems could be especially useful for centres without dedicated stroke specialists.

  • Any decision assistance tools must be validated and applied appropriately, and clear guidelines are needed to define how useful systems are in clinical practice.

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