Mobile app can help manage uncontrolled asthma

A mobile app can help manage uncontrolled asthma by measuring lung function and giving feedback in the form of automated and doctor-prescribed treatment recommendation, say researchers.
People suffering from uncontrolled asthma frequently experience breathing difficulties or asthma attacks and inadequate management and or correct use of medicine are common causes of this situation.

A study by researchers found that a treatment adjustment algorithm based on lung function and symptoms in a mobile phone can be an efficient tool in managing uncontrolled asthma.

For fuss-free measuring of lung function, the phone connects to a wireless spirometer and the app can register respiratory symptoms and provide visual feedback on treatment, said researchers, in a paper recently published.

The system called ' AsthmaTuner" analyses lung function and symptoms in accordance with asthma-care guidelines, said the research leader.

The users also receive a picture of the inhaler that is to be used and instructions on whether the medication is to be maintained, increased or decreased, he added.

AsthmaTuner enables the measuring of lung function via a wireless spirometer connected to a mobile-phone app.

The study comprised 77 uncontrolled asthma sufferers aged 6 onwards. Around half of these were children and adolescents.

We could see that asthma symptoms improved more with the digital tool than they did with traditional care. Adult patients who used the tool at least once a week also more often remembered to take their medicines, he said.

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: A mobile app can help manage uncontrolled asthma by measur ..

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A mobile app can help manage uncontrolled asthma by measurin ..

Read more at:
https://www.gadgetsnow.com/tech-news/mobile-app-can-help-manage-uncontrolled-asthma-study/articleshow/70960329.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst

Home Health This AI approach accurate than doctors at detecting cervical cancer

Researchers have developed a novel Artificial Intelligence (AI)-based computer algorithm that can identify cervical cancer with greater accuracy than a human expert, an advance that could revolutionise screening, particularly in low-resource settings.

The algorithm, called automated visual evaluation, can analyse digital images of a cervix and accurately identify precancerous changes that require medical attention.

It can be performed with minimal training, making it ideal for countries with limited healthcare resources where cervical cancer is a leading cause of illness and death among women.

Importantly, the automated visual evaluation identified precancer with greater accuracy than a human expert review or conventional cytology, the researchers said.

"Our findings show that a deep learning algorithm can use images collected during routine cervical cancer screening to identify precancerous changes that, if left untreated, may develop into cancer," said a researcher.

"In fact, the computer analysis of the images was better at identifying precancer than a human expert reviewer of Pap tests under the microscope (cytology)," he said.

Pap test is the cervical screening test.

To create the algorithm, the research team used more than 60,000 cervical images and included more than 9,400 women.

The findings, showed that overall, the algorithm also performed better than all standard screening tests at predicting all cases diagnosed.

"When this algorithm is combined with advances in HPV vaccination, emerging HPV detection technologies, and improvements in treatment, it is conceivable that cervical cancer could be brought under control, even in low-resource settings," the researchers said.

Further, the team plans to train the algorithm on a sample of representative images of cervical precancers and normal cervical tissue from women in communities worldwide, using a variety of cameras and other imaging options. 

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