Key Takeaways:
- The first thing to remember about building healthcare AI applications is that there are many different platforms and development options under this umbrella term.
- The more good quality, curated training data is available, the more you can shorten the timeline for training healthcare AI algorithms.
- CloudAutoML, IBM’s Watson, Viz.ai, Enlitic, Regard, and Twill are some of the platforms to look for to train healthcare AI algorithm.
- While hiring healthcare AI consulting company, make sure that you work with someone who can build an application that doesn’t conflict with your existing systems.
- While hiring healthcare AI consulting company make sure that they have a deep understanding of business process and how to map specific solutions.
Machine learning has been a growing technology for more than a decade, but recent media coverage has drawn more attention to the entire suite of artificial intelligence (AI) technologies, and resulting in an increase in AI Consulting companies.
From chatbots to facial recognition, AI has developed to the point where it offers direct, measurable healthcare benefits. AI lets you work smarter by giving you smart technology to work with.
As per statistics, the healthcare AI market is anticipated to reach around $188 billion by 2030. Not only this, the MGMA Stat poll revealed that 58 percent of the medical group leaders pointed out positive outcomes for healthcare AI – around 30 percent said that innovation would be the most defining trait for healthcare AI.
There’s so much that AI can give to the healthcare sector, so why not leverage it to augment patient experience and satisfaction? Why not use AI to reduce physician burnout rates? All you need to do is look for a reliable partner who would help you develop quality AI application.
So, here are a few things to look for when you start shopping for an expert healthcare AI consultant to help with your AI application project.
1. Types of Healthcare AI Technology
The first thing to remember while hiring healthcare AI consulting company is – building healthcare AI applications is that there are many different platforms and development options under this umbrella term. Everything from the coding language used, to the training library available, will affect the final performance of your healthcare AI application.
Healthcare AI consultants stay on the cutting edge of the technology, leaving behind cumbersome if/then statements for more flexible and versatile NLP (Natural Language Processing). The first AI experiments used if/then frameworks to create trees of possible actions.
Now, data scientists are leaving this modality behind as they develop less brittle programming that can handle more intuitive tasks. Ask about the type of AI technology on offer and how it will scale moving forward.
Here are some of the key AI technologies that can augment an AI application:
- Generative AI: The launch of ChatGPT, Dall-E, the generative AI landscape has skyrocketed in 2023. It has already left its mark in correcting errors in medical documents and enhancing images in radiology.
- NLP: There are so many benefits to using NLP – voice to text ability is significantly used by physicians to make notes during consultations. Additionally, this is a reliable technology for converting unstructured medical data into structured format. Let’s not forget sentiment analysis which aids physicians in emphasizing with patients, and classification of at-risk patients based on keywords.
- Machine Learning: This AI technology is known to collect surplus patient data and analyze it for further diagnosis and treatment outcomes.
- Predictive Analytics: This is a method that leverages artificial intelligence algorithms to predict population health – epidemics and pandemics. It is also a reliable way to predict whether a person is at-risk of lethal diseases. It acts like a preventive measure for people who may suffer from chronic conditions at a later stage in life.
- Chatbots: AI-driven chatbots are known to offer 24/7 service to patients. They can answer queries and book appointments. They can also send reminders for medication intake, appointments, and prescription refills.
These are some of the AI technologies that are likely to capture the healthcare market in the upcoming years. So, you need to decide which type of AI technology will benefit your organization and users, or what kind of AI technology you wish to develop. According to your answer, hire a healthcare AI consulting company that can develop the application for you.
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2. Access to a Wealth of Training Data
The next thing to note while hiring healthcare AI consulting company is surplus training data. One of the biggest barriers to entry with healthcare AI development is the training time. It takes hundreds of hours and hundreds of terabytes of data to train an AI to do a single thing – like consistently recognize an apple.
The more good quality, curated training data is available, the more you can shorten that timeline. One of the roadblocks lies in finding image data that has been properly tagged for the system to use. Discuss the availability of existing libraries and the need to develop specific training data with your consultant.
You’ll want to know what you need to provide versus what they already have available and how long it will take. While it is impossible to be specific, an expert should be able to get in the ballpark with an estimate.
Note: Healthcare data or ePHI is highly private, hence ensure that the AI consultant has a prior consent for using healthcare data to train algorithms.
3. Knowledge of Neural Networks
When building a network, you need an expert on network architecture. The same is true when you’re building a neural network for your AI. Neural networks are the foundation of your system, containing thousands of nodes full of historical data. How these nodes interact and transmit information determines the eventual output from your healthcare AI application.
This architecture is also what allows AI to learn and define criteria based on data. In an image training program, simply providing thousands of pictures labeled apple or no apple, allows the system to understand what to look for in an image. Similarly, for identifying hypertension in patients, AI needs to be trained for identifying patients with and without the condition.
4. Types of Healthcare AI Training
There are lots of options out there for training a healthcare AI application. New automation technologies make it easier than ever. Google released CloudAutoML, and IBM put Watson on the market for business use. Both of these platforms help streamline and fast forward the healthcare AI training process. Other than this, Viz.ai, Enlitic, Regard, and Twill are some of the other platforms to lookout for to train healthcare AI algorithm.
When working with a healthcare AI development agency, you’ll want to know what platform they use and about their expertise in this area of development. After all, an AI is not a contained system. It must work with all of your infrastructure both physical and in the cloud.
5. Blending Cloud, IoT, and Networking Requirements
Engineering systems that integrate with your existing cloud, IoT, and network is a challenge for new entrants into healthcare AI development. While hiring healthcare AI consulting company, make sure that you work with someone who can build an application that doesn’t conflict with your existing systems.
You want something that will pull data and present solutions, not only act on a limited data set available through your network, missing everything stored on the cloud.
6. Niche Expertise in the Healthcare Industry
When you find an expert healthcare AI consultant, that means you’ve found an exceptional engineer. Unfortunately, not all engineers can translate theoretical knowledge into real world solutions. While hiring healthcare AI consulting company make sure that they have a deep understanding of business process and how to map specific solutions.
AI automation has a lot of potential, but systems need to be purpose-built with a specific goal in mind. That often means performing internal assessments, and working with an AI consultant that also has management consulting experience.
Few businesses have the in-house expertise to tackle a healthcare AI development project, and even fewer have the deep pockets need to invest in machine learning from scratch.
That’s why development agencies offer the heavy lifting needed to get your project off the ground. From streamlined accounting to self-service HR to more complex systems like customer service or credit offerings, AI can be a major player.
The challenge lies in finding the right team to help teach an AI the skills needed to understand and adapt to changing conditions. Arkenea is just the right AI consulting company who are known to tackle top-class healthcare AI projects. Our contribution to healthcare software development for more than 13 years make us experts in the field, hence we can offer AI applications that fit the bill. Our AI offerings ranges from generative AI to predictive modeling. We deliver products that not only meet your requirements, but also match industry standards. To know more just hop on to a consultation call with us today.