AI Tools for Healthcare: Use Cases & Challenges 

AI tools for healthcare refer to various applications that harness natural language processing and machine learning. They are highly versatile: AI healthcare tools can simplify scheduling, bolster telemedicine services, and aid in diagnosis. 

In this article, we’ll cover: 

• What AI tools in healthcare are and the tasks they execute

• Common uses of AI in healthcare examples 

• Some top healthcare tools leading the space

• Medical AI pitfalls and how building your own healthcare tool can help

• Some frequently asked questions

• Why you should pick Blaze.tech as your AI healthcare platform

Let’s now discuss what AI tools for healthcare are. 

‍

What Are AI Tools for Healthcare?

AI tools for healthcare are software, applications, and systems powered by NLP, machine learning, and algorithms. These technologies enable your healthcare tools to understand plain English and draw upon enormous databases to respond to queries. 

These platforms can produce text and summaries, diagnose disease, or recommend treatment options based on how specific patient data relates to average datasets. AI tools have been shown to effectively assist healthcare professionals in delivering higher-quality care and providing more accurate diagnoses. 

But medical AI tools don’t stop at aiding physicians and medical professionals. They also help execute administrative healthcare tasks and bolster productivity for your front desk and IT teams. 

Common Use Cases of AI in Healthcare

Looking for specific examples of how medical AI can help? Let’s take a look at some popular use cases of AI in healthcare:

Clinical Decision Support

AI-powered clinical decision support systems help physicians interpret diagnostic images like X-rays, CT scans, and MRIs faster and more accurately. These tools can flag abnormalities and suggest possible diagnoses, acting as a second opinion. 

Another key application is predictive diagnosis. AI can analyze a patient’s medical history, genetics, and symptoms to identify risk factors before symptoms become critical.

Patient Engagement 

AI telehealth platforms transform patients' interactions with healthcare systems by providing immediate, around-the-clock support. They engage patients through text or voice interfaces, collecting symptoms, answering basic questions, and offering preliminary assessments. 

Scheduling and Intake 

AI tools can automate these processes, reducing manual input and human error. For scheduling, AI systems analyze provider availability, patient preferences, and visit types to book appointments with minimal back-and-forth. 

On the intake side, digital AI assistants collect patient data and pre-fill forms, verify insurance, and flag missing information before a visit begins.

Medical Record Analysis and Note Summarization

One of the most time-consuming parts of a clinician’s job is dealing with electronic health records (EHRs) and documenting patient visits. Because of NLP, AI tools can analyze unstructured notes, lab reports, and historical records to find highly relevant information. 

For documentation, some AI tools even generate clinical summaries or visit notes based on voice recordings or real-time inputs, reducing hours of typing and transcription.

Risk Scoring and Population Health

By analyzing EHR data, claims, social determinants of health, and wearable device inputs, AI can predict which patients will likely develop chronic conditions, require hospitalization, or fail to adhere to treatment plans. 

Risk scoring models use these insights to assign a numerical score indicating the likelihood of a future issue. This allows providers to intervene earlier, personalize treatment plans, and strategically allocate resources. 

These insights can also contribute to public health on a broader scale: Health systems can track population trends, monitor care gaps, and assess which communities may need more support.

Remote Monitoring and Virtual Care

AI provides telemedicine features, allowing remote patient monitoring and virtual care programs. Remote monitoring starts with wearables, home devices, and mobile apps that collect real-time heart rate, blood pressure, glucose levels, and more data. 

After collecting data, AI systems analyze these readings to detect anomalies and alert clinicians when they’re found. For example, an AI model monitoring COPD patients might send alerts when breathing patterns worsen, prompting earlier clinical intervention. 

In rural or underserved areas, AI-powered remote care can reduce the need for travel. Patients can communicate questions or get prescriptions filled directly from mobile devices.

‍

5 Popular AI Healthcare Tools 

Curious about some actual AI-powered healthcare platforms? Here are some of the 5 market leaders: 

1. Blaze

Blaze is a no-code platform for building web apps, scheduling tools, healthcare inventory management platforms, and dashboards without writing code. Its intuitive drag-and-drop interface makes it easy for non-technical users to launch powerful applications for healthcare workflows.

Blaze is HIPAA-compliant, so it can create medical apps that hold sensitive patient information. 

The platform uses AI to streamline tasks like auto-generating content, summarizing data, and suggesting logic flows based on user goals. Blaze’s built-in AI assistant helps guide app-building decisions and accelerates development speed — there’s a reason it’s called “Blaze.”

Some standout features include database integration, real-time collaboration, dynamic forms, and API connectivity. You can also trigger automations, design custom UIs, and connect to tools like Google Sheets, Salesforce, and OpenAI for more innovative app functionality.

‍

2. Merative

Merative, formerly IBM Watson Health, is an advanced AI-driven platform that offers data analysis, cognitive computing, and personalized care solutions. It integrates with EHR systems and medical literature to process vast amounts of medical data, making it usable for providers, insurers, and researchers.

The tool employs machine learning, NLP, and predictive analytics to provide evidence-based insights for diagnostics, treatment recommendations, and population health management. Key features include a medical imaging feedback and analysis functionality and Zelta, a data-management platform for clinical trials. 

The HIPAA-compliant platform is excellent for hospitals, providers, insurers, researchers, and pharmaceutical companies with complex data needs.

‍

3. Aidoc

Aidoc is a popular AI-powered healthcare platform specializing in medical imaging and care coordination. Its proprietary aiOS™ platform and CARE™ AI systems employ machine learning and deep convolutional neural networks to analyze real-time medical imaging data, flagging abnormalities and facilitating faster diagnosis. 

The platform coordinates care through early detection of aneurysms, management of pulmonary embolisms, and ensuring follow-up care for patients with incidental findings. 

The HIPAA-compliant platform appeals mainly to cardiologists, radiologists, and neurologists, with specific solutions built for these specialties. 

‍

4. Google Health

Google uses AI across platforms like Google Health and Google Cloud to improve healthcare delivery, diagnostics, and patient engagement. It integrates generative AI models like Gemini and MedLM into tools like Vertex AI Search for Healthcare and wearable devices to make healthcare more personalized and accessible. 

This HIPAA-compliant platform can execute a myriad of tasks. It analyzes complex patient records, interprets imaging data, and assists clinicians in diagnostic reasoning. It can also use conversational AI to gather patient histories and support differential diagnoses, while offering personal health recommendations through integrations with wearables like Fitbit.

Ideal users include clinicians, researchers, pharmaceutical companies, hospital administrators, and individual patients seeking personalized health insights. 

‍

5. Nuance (by Microsoft)

Now part of Microsoft, Nuance focuses on improving productivity in healthcare and other industries through voice AI, data analysis, and transcription. Its solutions, such as Dragon Medical One and Dragon Ambient eXperience (DAX), integrate seamlessly into clinical workflows to reduce administrative burdens, bolster documentation accuracy, and improve clinician-patient interactions. 

DAX converts doctor-patient conversations into structured medical notes in real time, while its speech recognition tools enable voice-driven navigation and data entry in electronic health records (EHRs). Built on Microsoft Azure, Nuance’s AI capabilities are continuously refined through billions of user interactions.

Ideal users include large healthcare organizations, which benefit most from Nuance's scalability and seamless integration with EHR systems, which amplify the workflows of both providers and IT professionals.

‍

Common Challenges Most Teams Face with AI Healthcare Tools

Although AI tools for healthcare promise smarter workflows and better patient outcomes, many fall short in real-world settings. These tools may appear helpful, but implementing them into your specific environment can be challenging. 

Here are a few challenges to be aware of when using an AI healthcare tool:

• Customization and integration are difficult: Many healthcare AI tools sound great on paper but are complex to tailor to real-world clinical workflows. Indeed, most of these are “one-size-fits-all” solutions, which don’t provide much leeway when adapting to your system.

• Developers are expensive: The catch-22 about paying developers to custom-make your own healthcare software with AI is the price. Unfortunately, hiring out developers to build your own private software can cost in the $100,000s. Even if you’ve budgeted for such an expense, you’ll need to set aside considerable time communicating with the development agency and await different iterations. 

• HIPAA compliance isn’t always baked in: Some platforms claim to be medical AI and deliver impressive features, like note summarization or risk prediction. Unfortunately, they may not meet HIPAA standards — and non-HIPAA-compliant software is a no-go if you’re handling sensitive patient data.

Unfortunately, these challenges are a dealbreaker for specific clinics, and instead of upgrading their systems, they continue using legacy technology. However, there is a better option.  

‍

Build Your Own AI-Powered Healthcare Tool with No-Code

How does a company meet the above challenges? One way is to create your own healthcare platform. And here’s the main selling point: You can build it without any programming knowledge or technical background. 

No-code development platforms like Blaze make this possible. Blaze is HIPAA-compliant, making it an excellent fit for creating healthcare software. As a bonus, Blaze also offers robust AI tools that contribute to your platform’s overall functionality and user experience. 

Instead of writing in line after line of code, you’ll use a drag-and-drop interface, which functions like photo-editing software. Here’s a quick guide that demonstrates how no-code development platforms work:

1. Build your database: Your database will serve as your healthcare app’s primary foundation. If you’re starting from scratch, pick a tool like Blaze that provides its own database builder. But Blaze also integrates with popular database providers like MySQL, Xano, Airtable, and others, so you can connect your data in just a few clicks.

2. Create your frontend: First, you can select a premade template that reflects the type of app you’re building, such as one for scheduling, inventory management, etc. Then, drag over pre-made components like calendars, forms, and buttons to your desired place.  

3. Add AI functionality: Create functions like AI-powered chatbots that can book appointments, answer questions, transcribe or summarize clinical notes, and help with billing. 

We can’t emphasize enough the level of customization you’ll get when you utilize a no-code app builder like Blaze. Customizing your no-code healthcare platform to fit your needs and automate workflows is much easier than using a one-size-fits-all platform — and at a much lower cost than traditional development.   

‍

Frequently Asked Questions

Can AI Be Used in Hospitals?

Absolutely. Hospitals increasingly use AI to improve diagnostics and patient engagement, automate documentation, and streamline operations. Tools like AI-driven imaging analysis, predictive risk scoring, and virtual assistants help clinicians deliver faster and more accurate care. 

Does Blaze Support HIPAA Compliance Out of the Box?

Yes, Blaze is HIPAA-compliant right out of the box, making it an ideal choice for building healthcare applications that handle sensitive patient data. This built-in compliance ensures that any tool you create, for scheduling, patient intake, or clinical dashboards, adheres to stringent data privacy and security regulations. 

Can I Use Blaze to Build Patient Apps?

Definitely, Blaze allows you to build fully functional patient apps without writing a single line of code. You can design patient intake forms, appointment booking tools, AI-powered triage bots, and secure messaging features. Best of all, Blaze’s HIPAA compliance ensures patient data is kept safe while offering a user-friendly experience for patients and providers.

What AI Tools Can Be Used With Blaze?

Blaze offers built-in AI tools through its native OpenAI (ChatGPT) integration, which can be used for content generation, note summarization, and chatbot interactions. 

Can Blaze Integrate With Existing EHRs or Health Databases?

Yes, Blaze can integrate with existing EHRs and health databases using its API connectivity and database support. Blaze enables secure, real-time data exchanges if you're working with MySQL, Airtable, Xano, or custom EHR platforms. 

This means your new app can sync with existing systems to pull patient records, update appointment statuses, or trigger automated workflows, without disrupting your current infrastructure.

‍

Start Building Your AI Tool for Healthcare with Blaze

Although making your own AI-enabled healthcare applications might sound tough, using a no-code platform like Blaze simplifies the process. Here’s how Blaze can rocket your app building:

• Blaze features an AI-enabled drag-and-drop interface that harnesses OpenAI’s ChatGPT-4o to organize data or power chatbots. 

• To start your app building on the right foot, you’ll have access to prebuilt templates and elements that you can customize to meet your workflows. These support creating appointment forms, inventory management, and more.

• As soon as you sign up with Blaze, their helpful implementation team will immediately take you under their wing. They’ll ensure that you know how to use the platform and teach you about every in and out, so you won’t encounter any headaches. And when you finish creating your AI healthcare tool, they’ll ensure it gets published and runs flawlessly. 

Importantly, Blaze is HIPAA-compliant, so your patients’ sensitive data will be on lockdown. Ready to start building AI-powered tools for your healthcare business fast? Schedule a demo and try Blaze today.