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Eva8 [605]
2 years ago
15

machine learning provides an accurate prognostication model for refractory overactive bladder treatment response and is noninfer

ior to human experts
Social Studies
1 answer:
Rina8888 [55]2 years ago
3 0

A rising amount of clinical data may become too much for a doctor to manage on their own in order to make the best decisions. We sought to create algorithms to predict patient outcomes following the overactive bladder treatments onabotulinumtoxinA (OBTX-A) injection and sacral neuromodulation using an unique machine learning (ML) approach (SNM). In order to predict outcomes like treatment response and a decline in urge incontinence events in the OBTX-A and SNM cohorts, novel ML algorithms were created and given the task of doing so in test and validation sets.

In terms of accuracy, novel ML systems outperformed expert urologists at predicting OBTX-A outcomes and were comparable at predicting SNM outcomes. Since some parts of the doctor-patient relationship are nuanced and imperceptible, ML may supplement a doctor's clinical judgement rather than taking its place.

<h3>What is the short definition of machine learning?</h3>

Artificial intelligence, which is widely defined as a machine's ability to mimic intelligent human behaviour, includes the subfield of machine learning. Artificial intelligence (AI) systems are used to carry out complicated tasks in a manner akin to how people solve issues.

To learn more about Machine learning visit:

brainly.com/question/16042499

#SPJ4

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Which argument is an accurate indication of why the speaker of the house is considered the most powerful person in the house of
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psychologist is interested in constructing a 95% confidence interval for the proportion of people who accept the theory that a p
ch4aika [34]

Answer:

A.We therefore have with 95% confidence the proportion of all people who accept the theory that a person's spirit is no more than the complicated network of neurons in the brain is between 0.0555 and 0.0884

B. About 95 percent of these confidence intervals will contain the true population of all the people who accept the theory that a person's spirit is no more than the complicated network of neurons in the brain and about 5 percent will not contain the true population

Explanation:

The parameters given are;

The number of persons who accept the theory that a person's spirit is no more than the complicated neurons in the brain, x = 68

The sample size, n = 945

Therefore, we have the confidence interval, CI, given as follows;

CI=\hat{p}\pm z\times \sqrt{\dfrac{\hat{p}(1-\hat{p})}{n}}

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z value at 95% confidence level = 1.96

We therefore have;

CI=0.07196\pm 1.96\times \sqrt{\dfrac{0.07196(1-0.07196)}{945}}

Which gives the 95% confidence interval as follows;

0.0555 < \hat p < 0.0884

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Answer:

differences

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