Google’s this Tool can easily understand your Doctor’s bad handwriting

New Delhi: It’s an evergreen joke that nobody can read a doctor’s handwriting, not even the doctor!

Well, health professionals do write prescriptions in a rushed manner as they work long hours, attending several patients in a day.

And then it becomes quite difficult to understand or even identify the medicines mentioned in the prescription, and to make that task simple and easy, Google is working on a model that will smoothly read your doctor’s badly handwritten prescriptions.

Google announced an artificial intelligence (AI) and machine learning (ML) model that can identify and highlight medicines within difficult-to-read handwritten prescriptions.

During its annual conference being held in India, Google announced that it is working with pharmacists to find ways to decode handwritten notes by doctors.

The feature is currently a research prototype and not available to the general public yet. But as per what we know so far, the feature will allow users to either take a picture of the prescription they want to be decoded or upload a picture from their photo gallery.

Once the picture is uploaded, Google’s app will identify and highlight the medicines mentioned in the prescription.

According to the tech giant, this feature will act as an assistive technology for digitizing handwritten medical documents by augmenting the humans in the loop, such as pharmacists, however, no decision will be made solely based on the output provided by this technology.

The AI tool will be created in Google Lens that can decode badly written medical notes. The company unveiled the feature during its ‘AI for India’ event here.

“Much work still remains to be done before this system is ready for the real world,” Google said.

The tech company’s Lens feature can be used to detect objects (such as plants and animals) and translate languages.

At the event, Google also announced its working on ways to harness advanced AI and ML capabilities along with remote sensing technology, to develop a model that can help generate a holistic understanding of India’s agricultural landscape.

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