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The technology, developed by Pittsburgh, Pennsylvania startup Abridge, aims to reduce workloads for clinicians and improve care for patients. Shivdev Rao, the company’s CEO and a cardiologist, told The Register doctors can spend hours writing up notes from their previous patient sessions outside their usual work schedules.

“That really adds up over time, and I think it has contributed in large part to this public health crisis that we have right now around doctors and nurses burning out and leaving the profession.” Clinicians will often have to transcribe audio recordings or recall conversations from memory when writing their notes, she added.

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Abridge’s software automatically generates summaries of medical conversations using AI and natural language processing algorithms. In a short demo, The Register pretended to be a mock patient talking to Rao about suffering from shortness of breath, diabetes, and drinking three bottles of wine every week. Abridge’s software was able to note down things like symptoms, medicines recommended by the doctor, and actions the clinician should follow up on in future appointments.

The code works by listening out for keywords and classifying important information. “If I said take Metoprolol twice, an entity would be Metoprolol, and then twice a day would be an attribute. And if I said by mouth, that’s another attribute. And we could do the same thing with the wine example. Wine would be an entity, and an attribute would be three bottles, and other attribute every night.”

“We’re creating a structured data dataset; [the software is] classifying everything that I said and you said into different categories of the conversation. But then once it’s classified all the information, the last piece is generative.”

At this point, Rao explained Abridge uses a transformer-based model to generate a document piecing together the classified information into short sentences under various subsections describing a patient’s previous history of illness, future plans or actions to take.

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Physicians can edit the notes further, whilst patients can access them in an app. Rao likened Abridge’s technology to a copilot, and was keen to emphasize that doctors remain in charge, and should check and edit the generated notes if necessary. Both patients and doctors also have access to recordings of their meetings, and can click on specific keywords to have the software play back parts of the audio when the specific word was uttered during their conversation.

“We’re going all the way from the summary we put in front of users and we’re tracing it back to the ground truth of the conversation. And so if I have a conversation, and I couldn’t recall something happening, I can always double-check that this wasn’t a hallucination. There are models in between that are making sure to not expose something that was not discussed.”

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Source: US hospital rolls out AI ‘copilot’ for doctors’ paperwork • The Register

Microsoft on Tuesday announced that it is using an advanced version of Open AI’s DALL-E image generator to power its own Bing and Edge browser. Like DALL-E before it, the newly announced Bing Image Creator will generate a set of images for users based on a line of written text. The addition of image content in Bing further entrenches its early lead against competitors in Big Tech’s rapidly evolving race for AI dominance. Google announced it opened access to its Bard chatbot the same day, nearly a month after Microsoft added ChatGPT to Bing.

“By typing in a description of an image, providing additional context like location or activity, and choosing an art style, Image Creator will generate an image from your own imagination,” Microsoft head of consumer marketing Yusuf Mehdi said in a statement. “It’s like your creative copilot.”

For the Edge browser, Microsoft says its new Image creator will appear as a new icon in the Edge sidebar

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Source: Microsoft Adds DALL-E AI Image Generator to Bing

Today we’re starting to open access to Bard, an early experiment that lets you collaborate with generative AI. This follows our announcements from last week as we continue to bring helpful AI experiences to people, businesses and communities.

You can use Bard to boost your productivity, accelerate your ideas and fuel your curiosity. You might ask Bard to give you tips to reach your goal of reading more books this year, explain quantum physics in simple terms or spark your creativity by outlining a blog post. We’ve learned a lot so far by testing Bard, and the next critical step in improving it is to get feedback from more people.

About Bard

Bard is powered by a research large language model (LLM), specifically a lightweight and optimized version of LaMDA, and will be updated with newer, more capable models over time. It’s grounded in Google’s understanding of quality information. You can think of an LLM as a prediction engine. When given a prompt, it generates a response by selecting, one word at a time, from words that are likely to come next. Picking the most probable choice every time wouldn’t lead to very creative responses, so there’s some flexibility factored in. We continue to see that the more people use them, the better LLMs get at predicting what responses might be helpful.

While LLMs are an exciting technology, they’re not without their faults. For instance, because they learn from a wide range of information that reflects real-world biases and stereotypes, those sometimes show up in their outputs. And they can provide inaccurate, misleading or false information while presenting it confidently. For example, when asked to share a couple suggestions for easy indoor plants, Bard convincingly presented ideas…but it got some things wrong, like the scientific name for the ZZ plant.

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Source: Sign up to try Bard from Google