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Three ways ML & AI are impacting healthcare 

Evan Davey
Evan Davey
Head of Australia & NZ
Length
4 min read
Date
11 September 2024
Kali app

Detecting heartbeat anomalies during pregnancy 

Kali Healthcare is on a mission to improve pregnancy outcomes, especially for remote or disabled individuals. They do this via sensors that collect data about a woman and baby’s heartbeat and other vital signs. By analyzing this data, Kali hopes to “provide insights into predicting pregnancy complications.” 
 
We supported Kali by creating an easy-to-use digital platform experience, which ensures patients and healthcare professionals can access the information they need quickly and efficiently.

More specifically, we embraced machine learning to create a monitoring system with capabilities for real-time data analytics. The ML model can analyze large data sets to detect unusual heartbeat rhythms and then send alerts to doctors immediately. 

Kali healthcare

Converting medical notes into official documentation

Doctors spend as much as 38% of their weekly working hours writing documentation. This excessive workload leads to stress, burnout, and heightened concerns about potential errors in patient records. We recently worked with a startup looking to solve this problem with a purpose-built AI tool. The tool would allow doctors to create and use templates to quickly and easily convert their notes into detailed medical documents. 

There were a few things that made building this product a challenge. 

  •  Doctors have a particular style and approach to documentation and value that ownership
  • To ensure no sensitive information is at risk, all personal patient data must be de-identified before being processed 

We leveraged Gen AI to de-identify data against doctor-defined templates, which minimized the medical context of Gen AI usage. Using ChatGPT 4 and AWS, we are working towards an MVP alongside our client. 

Clair AI AP UXUI

Helping clinicians search faster than before 

The Clair AI app from Caryheatlh is geared toward clinicians. It helps them access the latest pharmaceutical and medical information. 

Considerations for this project included transparency and familiarity with AI. We needed to make sure clinicians knew how to create prompts and had confidence in the results. 

To address these challenges, we balanced AI responses with the raw data powering them and added the option of follow-up questions for further justification. We also included a search function in the app that offers open-ended and guided searches to help medical professionals find information quickly. 

Clair AI AP UXUI

Innovation with AI 

Historically, the healthcare industry has been slow to innovate. And while skeptics abound, we believe that AI is the technology that will encourage and accelerate innovation in this industry. 

As you experiment with AI, start with the following criteria for your proof of concept. You want to test AI and ML functionality that is high impact, low risk, and involves communication. 

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