AI In Healthtech: 5 Use Cases, Future Trend, And More

With the help of our guide on AI in HealthTech, welcome to the cutting edge of healthcare innovation. Discover five fascinating applications of artificial intelligence that are having a big impact, from tailored treatment plans to accurate diagnosis. Examine the upcoming developments that could reshape the healthcare industry and lead to more patient-centered and effective methods. Our in-depth guide explores the exciting nexus between health technology and artificial intelligence (AI), illuminating the revolutionary potential of AI to revolutionize healthcare delivery.

• The Top AI Cloud Platforms for Medical Applications
• Top 5 Use Cases of AI in Healthcare
• How to Integrate AI Platforms Into Websites, Systems, and Software for Healthcare
• The Future of AI in Healthcare

The Top AI Cloud Platforms for Medical Applications

Is implementing AI technology really possible for a medical services provider like a community health center, private clinic, or boutique physician? Let’s look at several instances of artificial intelligence (AI) in the healthcare industry, along with a list of well-known vendors who are improving their AI platforms to make AI and ML services more affordable for a wider spectrum of healthcare organizations, including health-tech startups.

• AI Services from OracleOracle Cloud Infrastructure (OCI) AI Services provides chatbots, language processing, speech recognition, computer vision, prediction, and forecasting capabilities, with an emphasis on data scientists and developers.
• IBM WatsonIBM provides scalable cloud-based medical data analytics and AI solutions in addition to AI-based cognitive services and applications. IBM continues to be at the forefront of healthcare AI breakthroughs by utilizing a strong cloud platform.
• Developers can access a wide range of prebuilt SDKs, customized services, and APIs for vision, language, speech, decision-making, and search with Microsoft Azure Azure Cognitive Services. Furthermore, Microsoft Azure provides strong frameworks and tools for machine learning.
• Cloud AI by GoogleSmooth machine-learning solutions are made possible by Google Cloud AI’s seamless integration with services like Google BigQuery and Google Dataflow. AI applications in the healthcare industry can benefit from AutoML since it makes it possible to create unique machine learning models with little to no coding.
• OpenAIModern language models are available through OpenAI’s API, which can be used to enable natural language understanding in healthcare applications, generate medical reports, summarize patient records, and help with clinical decision-making. 
• AI Services on AmazonWith its machine learning-based business prediction tools for non-technical analysts, AWS serves the needs of data scientists and AI engineers. AWS delivers a dependable ecosystem for healthcare AI applications with its strong language capabilities (including translation services) and uniform interface and APIs across all of its cloud services.

Top 5 Use Cases of AI in Healthcare

We will look at particular AI use cases in healthcare in this section. These examples might sound novel or even revolutionary, yet they are increasingly being used in company operations and medical care across a variety of domains. These useful apps can also be integrated with systems utilized in small- to medium-sized healthcare practices and IT environments. It’s crucial to thoroughly examine each of the following AI use cases if your healthcare institution or business is thinking about implementing an AI solution.

Use Case #1: Intelligent Chatbots for Customer Care: Conversational AI Implementation in Healthcare 

One significant advancement in medical technology is conversational AI. Its implementation is remarkably simple and user-friendly. Furthermore, it has been demonstrated that AI-powered chatbots, also known as voice assistants, are incredibly effective in healthcare workflows, simplifying procedures like these: 

• discussions with patients and answers to commonly asked questions (FAQs) with the capacity to provide further details or address subquestions.
• Online chat for symptom assessment that includes initial diagnosis based on anamnesis and the option to make an appointment with the right doctor or medical professional.
• voice-activated health aides for duties including monitoring medicine via apps and providing elderly patients with assistance through telehealth systems.
• after-treatment care and treatment plan implementation monitoring.
• In hospitals and healthcare teams, including travel nurse agencies and medical staffing marketplaces, internal communication and staff coordination are crucial.

Many chatbots can only provide basic answers to particular inquiries since they are programmed with rules and prepared responses. Conversely, more sophisticated and organic interactions are provided by conversational AI. 

• Through utilizing
• algorithms for machine learning,
• Natural language processing, as well as
• contextual knowledge,

Healthcare conversational AI systems are capable of carrying on complex, unpredictable dialogues that closely mimic human exchanges. They can adjust to various linguistic levels or styles, cover a wide range of topics, and answer a variety of queries. Since not all potential patients in the United States speak English as their first language or have adequate proficiency, this is very helpful in the healthcare industry.

The main applications of AI in healthcare are as follows: everything is made to automate administrative and patient communication jobs, freeing up more time for healthcare workers to engage in their primary duties. 

Use Case #2: Comparing Generic Internet Research with Symptom-checking Virtual Assistants 

Conversational AI can be an effective tool for facilitating medical triage and symptom-checking. When people have symptoms like chronic headaches or body aches in addition to other health issues, they frequently search online for information. They might, however, get worried or unclear about the reason behind their symptoms after seeing generic search results. Cyberchondria syndrome is a phrase specifically used to describe health issues and obsessive behaviors brought on by extensive online searches for possible illnesses and symptoms.   

Conversely, conversational AI systems offer individualised counsel and recommendations based on their unique circumstances. These systems assist patients feel less anxious by providing them with psychological as well as medical support in a kind and courteous manner. 

Through the use of conversational AI, patients can go through a comprehensive diagnosis procedure by answering questions about their symptoms and having a step-by-step conversation. This systematic approach guarantees a more precise comprehension of their state and aids in ascertaining the suitable degree of assistance required. Conversational AI can detect medical conditions quickly and accurately and help schedule appointments for follow-up examinations as needed, even though certain symptoms can hint to a critical ailment that needs to be treated right away.

Use Case #3: AI Chatbot for Information Distribution 

The COVID-19 epidemic has brought home a point that we have always known but frequently overlook: Panic and false information spread during a health crisis even more quickly than infection. Even in normal situations, though, people and communities can suffer when they are given misleading or erroneous information about health and illness. This can prevent people from making educated decisions or, worse, encourage them to make the wrong ones. 

The burden of educating the public and dispelling false information falls on medical experts, who have an increased workload during trying times. In order to relieve healthcare professionals of tedious patient communications, conversational AI can be a useful tool for automating a variety of medical PR tasks:

• AI helpers can spread awareness of health emergencies and issues.
• AI can give users rapid access to trustworthy and accurate information.
• Conversational AI can be used on a variety of digital channels, such as social media, messaging applications, and websites, guaranteeing that people have access to verified, critical information.

Use Case #4: Management, Tracking, and Coaching for Health 

It is almost impossible to have a personal healthcare team made up of a nutritionist, nurse, health adviser, and coach accessible around-the-clock to oversee and counsel you in maintaining a healthy lifestyle and making the right medical decisions, unless you are a multimillionaire. On the other hand, conversational AI has revolutionized patient care by giving people the ability to take charge of their physical health and feel as though they have a team of expert health management specialists at their disposal. 

Patients can efficiently monitor their health condition and seek timely medical and wellness advice through early symptom identification and online consultations with an AI-driven assistant who has access to the most recent medical knowledge base. Furthermore, patients may now take control of their own healthcare journeys because they have a multitude of tools and information at their disposal. They can easily keep track of important health indicators, oversee drug regimens, and get individualized advice and recommendations for leading healthy lives that include mental health, physical fitness, healthy eating, and weight management, among other things. 

Use Case #5: Automation to Simplify Administrative Tasks 

Many administrative duties are routinely completed in healthcare facilities, frequently with difficulties and inefficiencies. Medical staff personnel, for example, have to spend time looking for patient forms and going through several programs, which can cause frustration or confusion. Putting in place a clever AI-based platform might greatly enhance the subsequent procedures: 

• Documentation and data management: Medical personnel can enter data into electronic health record (EHR) systems, update medical records, and transcribe patient notes using voice recognition technology driven by artificial intelligence. Because AI may recommend corrections or automatically fill in pertinent fields based on context and historical data, this simplifies the documentation process, decreases the amount of manual data entry, and increases accuracy. 
• Information retrieval and search: With artificial intelligence (AI), personnel can search databases for particular patient data or medical literature using natural language processing. They can save time and effort by only speaking or typing their queries, and AI systems will promptly collect pertinent facts.
• Management and scheduling of appointments: Administrative staff might assign appointment-scheduling duties to AI-based virtual assistants. Employees can communicate with the virtual assistant by texting or calling in information about patient preferences, availability, and needed services. The AI system will then take care of scheduling effectively.
• AI-powered chatbots are capable of helping with patient triage, identifying early symptoms, and directing patients to the right department or healthcare provider. Employees can text or speak with the chatbot, which makes the patient triage procedure easy and effective.

How to Integrate AI Platforms Into Websites, Systems, and Software for Healthcare

Unprecedented prospects for higher operational efficiency, tailored treatments, and better diagnostics are presented by the incorporation of AI technology. 

This section will explore the practical methods and considerations associated with integrating AI solutions in the healthcare sector, laying the groundwork for a time when medical personnel and intelligent systems work together to deliver the best results for patients.

API Conversions 

It is essential to include high-level, user-friendly APIs into current healthcare IT systems in order to enable AI functionalities. APIs facilitate smooth data interchange and communication by serving as bridges between various components. 

Healthcare companies can take use of AI-powered features without having to make any changes to their current infrastructure by using reliable APIs. In this scenario, updating the user interfaces and back-end systems of healthcare software is required. 

Assist Skilled Tech Professionals 

Working together with knowledgeable IT partners is crucial to a seamless and effective AI deployment. Appic Softwares guarantees that healthcare businesses receive professional direction at every stage of the process by providing all-inclusive IT consulting services. Our group is capable of evaluating the current infrastructure, pinpointing areas in need of development, and creating a personalized AI integration roadmap.

Technical Measures for Healthcare AI Integration 

Data Preparation: Start by compiling pertinent medical data from clinical trials, imaging studies, and/or patient records. Make that the data complies with privacy laws like HIPAA and is appropriately cleansed, anonymized, and securely stored.

• Selecting an AI Model: Determine which particular healthcare use cases—precise, automated diagnostics, automated laboratory research management systems, and patient monitoring—are best suited for AI. Select the AI models that are most relevant for specific use cases, such as predictive analytical models for health risk assessment and deep learning algorithms for picture analysis (this can be a beneficial option for custom medical insurance administration systems.)
• Model Training: Using top-notch, labeled healthcare datasets, train the chosen AI models. In order to help the model understand patterns and generate precise predictions, this approach entails providing it with a variety of examples. Work along with domain specialists to make sure that models are trained with expert knowledge, such as doctors or medical researchers.
• Testing and Integration: Incorporate AI elements into the current websites, apps, and software for the healthcare industry. To verify the AI algorithms’ dependability, accuracy, and performance, do thorough testing. This covers testing in a simulated environment, testing in the real world using sample data, and getting input from medical experts.
• Deployment and Monitoring: Ensure a smooth integration with current workflows and systems by deploying the AI-powered solution in the healthcare setting. Maintain a close eye on the AI models’ performance and solicit user input. Establish systems for gathering and evaluating real-time data in order to track the efficacy and influence of the AI solution on both operational and patient results.

The Future of AI in Healthcare

Recent developments in health technology indicate that AI has enormous potential in the field of medicine and that its effects could be truly revolutionary. The following are some forecasts on AI’s role in healthcare:

• AI will make it possible to create extremely individualized treatment programs that are based on the individual genetic composition, way of life, and medical background of every patient. Patients of all socioeconomic levels can now afford a personalized approach to healthcare because of the extraordinary productivity that comes with AI technologies. As previously unthinkable as customized treatment sounded, this is a major change.
• AI will play a significant role in augmented decision-making by offering healthcare practitioners real-time insights, evidence-based suggestions, and predictive analytics to improve clinical decision-making. Health data visualization and automated medical data mining are involved in this. 
• AI-powered technologies will significantly improve the delivery of remote healthcare through telehealth and remote care. These technologies will enable virtual consultations, remote monitoring, and advanced diagnostic capabilities. Patients now have access to 3D-rendered virtual physicians powered by AI simulations thanks to telehealth AI. This makes it possible for them to participate in regular clinical and healthcare routines and receive timely consultations with less restrictions.  
• Evolution of genomic medicine: Through the analysis of intricate genetic data, the identification of disease markers, and the facilitation of tailored therapy, artificial intelligence will be important in realizing the promise of genomic medicine.

Conclusion

AI is revolutionizing health technology, as seen by improved diagnoses and more individualized medical treatment. Future healthcare innovation and efficiency are promised by the ongoing integration of artificial intelligence.

Moreover, if you are looking for a company through which you can hire dedicated AI developers then you should check out Appic Softwares. We have an experienced team of developers who have helped clients across the globe with AI development.

So, what are you waiting for?

Contact us now!