Improving Diagnostics with AI-powered Predictive Analytics in Healthcare

Improving Diagnostics with AI-powered Predictive Analytics in Healthcare

The collaboration of artificial intelligence (AI) with massive healthcare data is transforming the way care is delivered. At Oodles, we constantly innovate new therapeutics and strive to improve the existing ones by channelizing medical data using...

The collaboration of artificial intelligence (AI) with massive healthcare data is transforming the way care is delivered. At Oodles, we constantly innovate new therapeutics and strive to improve the existing ones by channelizing medical data using machine learning technologies. Recent years have witnessed a significant rise in the applications of predictive analytics in the healthcare sector for strengthening care decisions and facilities.

The underlying machine learning techniques of predictive analytics enable organizations to combat medical emergencies and take timely preventive measures. This blog post cumulates effective applications of AI development services for predictive analytics to improve health and healthcare.

Predicting Widespread of Chronic Diseases
In the face of rising population growth, it is cumbersome for medical authorities to track population health and take timely preventive measures. Inefficient risk prediction leads to the development of long-term chronic conditions that are difficult to treat and affect patient care drastically.

With advancements in machine learning capabilities, healthcare organizations are now beginning to infuse AI-powered predictive analytics in population health management. Here’s how big data analytics derive valuable insights for patient care-

A) Risk Score Prediction based on electronic health records (EHR), biometric data, lab test reports and social determinants of health provides in-depth health insights. Machines trained using this data can identify population sections with high-risk patients and signal doctors to plan relative interventions.

B) Prediction of extreme epidemic conditions is now possible with big data analytics, machine learning, and high computational power. Prediction of infectious diseases is done with various data sources such as weather reports, reported cases, population density, economic profile, etc.

Predictive analytics for epidemic conditions
Source: Medium

With big data analytics, machine learning models become a key source to improve healthcare services in highly prone regions. Accurate and efficient prediction of chronic diseases such as heart attacks and cancer can improve healthcare quality and cost significantly.

How does Oodles practice predictive analytics in healthcare to prevent chronic disease?
At Oodles, our AI team is skilled at deploying machine learning algorithms for data-driven predictive analytics. We have hands-on experience in training ML models with EHR, 2D, and 3D medical imagery to generate accurate health insights.

Our most recent AI solution for healthcare institutes combine machine learning libraries like Scikit-learn to develop a Diabetic Prediction System. The model works on structured data inputs such as Plasma Glucose, Tricep Thickness, and blood pressure to predict diabetes in patients.

The model’s USP is that it does not require any intervention of a physician to measure diabetes. Supported by a simplified interface, the system enables common individuals to test diabetes in an easy, quick, and accurate manner.

Ensuring Optimal Staff and Resource Allocation
Improper resource allocation and unbalanced distribution of healthcare facilities has been a major concern for hospitals in villages and suburban areas. Medical authorities often fail to judge unprecedented critical conditions and excessive demand for medical resources leading to overflowing emergency wards and mismanagement.

With the advent of AI-driven predictive analytics, healthcare institutes can streamline medical resource allocation by-

A) Predicting the fluctuations in patient flow to ensure proper bed allocation.

B) Rescheduling staff according to patient flow to enhance patient care effectively.

C) Detecting patterns of utilization from patient data to manage appointment rate and service.

Deploying AI-powered Predictive Analytics in Healthcare with Oodles AI
We, at Oodles, build industry-specific predictive engines for eCommerce, marketing, healthcare, and financial businesses. Our AI team enables healthcare organizations to channelize big data analytics to extract meaningful insights from complex medical records.

In addition, we have expertise in improving healthcare services with AI-powered conversational chatbot development. We enable doctors to automate remote assessment with natural language-based chatbots and other AI solutions.

Talk to our AI team to know more about our artificial intelligence services.

Artificial Intelligence (AI) Tutorial - Getting started with AI

Artificial Intelligence (AI) Tutorial - Getting started with AI

Artificial Intelligence (AI) Tutorial - Getting started with Artificial Intelligence. In this Artificial Intelligence tutorial you will learn end to end about AI and it's vast domain. So this AI tutorial for beginners is an exhaustive tutorial for you to get started with AI.

In this Artificial Intelligence (AI) tutorial you will learn end to end about AI and it's vast domain. So this AI tutorial for beginners is an exhaustive tutorial for you to get started with AI.

What is Artificial Intelligence (AI)? Understand AI in 5 minutes

What is Artificial Intelligence (AI)? Understand AI in 5 minutes

What is Artificial Intelligence (AI)? How Does AI Work? Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks the typically require human intelligence. Understand AI in 5 minutes, I give context on how to think about AI. What is AI?

There is so much discussion and confusion about AI nowadays. People talk about Deep Learning and Computer Vision without context. In this short video, I give context on how to think about AI.
What is AI?

Is Low-code or no-code development is future of mobile app development

Is Low-code or no-code development is future of mobile app development

Mobile app development has skyrocketed over these years with the increasing demand of mobile apps for a variety of purposes like entertainment, banking, weather update, health, booking movie tickets, booking a taxi etc. With the latest...

Mobile app development has skyrocketed over these years with the increasing demand of mobile apps for a variety of purposes like entertainment, banking, weather update, health, booking movie tickets, booking a taxi etc. With the latest technologies adopted by mobile app development services, there are different app development approaches which are being practiced. Among them is low-code or no-code development. But will it be the future of mobile app development? Will any mobile application development company start taking this approach as the primary one. Let’s try to find a detailed answer to this question.

But first, let’s understand what this approach exactly is? Well, it is a streamlined approach which involves swift design as well as development with minimal coding, generally relying on different third-party APIs.

Even though there isn’t any single definition of no-code or low-code development because it is actually more of a mindset rather than something which can be directly measured, this mindset has certainly led to a vast community mushrooming up with this mentality. Android app development services are rapidly adopted by this approach. Low-code app innovators are rapidly disrupting all types of various industries. There are a plethora of benefits to these low code platforms and let’s look at this.

1. Less Number of Bugs

It is pretty evident that less code actually means fewer bugs. As simple as that. The entire bug testing phase is actually a major part of modern and latest application development. It is quite inevitable that various issues will come up if there is actually enough code present there. But the best thing regarding low code platforms is that there’s certainly less to test. Also, when they actually tap into APIs, those particular APIs are actually tested by other people.

Lesser number of bugs is better for both users, as well as developers since less amount of time, will be taken up with bug-fixes and troubleshooting. Also, the fast pace of this development approach actually means that if in any case a bug is found, it is generally better just to develop a new iteration rather than fixing it.

2. Significant Lower Costs

Among the most obvious reasons for why you would actually opt for any low code platform is that in reality, low code results in lower cost. Low code development leads to faster app development which saves a lot of time and as a result, lower cost.

It's not only good for companies but also for developers. It certainly cut out the intermediaries, and while they charge less, they use fewer resources and finally come out on top. It is fun for developers because it stops them from actually finding themselves stuck on one particular project which seems to last forever. This is why most of the companies hire app developer who is a well-versed with low-code development.

3. Better Accessibility

The lesser amount of code an application uses, the lesser bandwidth is needed to download it as well as run it. This is quite good news for the people who are based in rural areas or in different developing countries where access to the internet isn’t as prevalent as Western countries. Also, as low code applications can easily be created quite easily than a traditional app, they can easily be released much more swiftly and at a much lower price, and sometimes for free. iPhone app development services follow this approach because it will help in increasing the uptake of their apps as it reduces the entry barrier for every person from lower-income families.

Innovative Development Approach

Among the most promising instances of a low-code or no-code platform is Uber. The apps tap into Google for Maps, Dropbox for storage, Braintree for payments and much more. The most interesting thing about this is that app programming interfaces of APIs which Uber actually relies upon are easily available to anyone who wishes to use them. Uber took those APIs and then used them to create, which was new without requiring to develop each of those particular individual elements, all by themselves. They developed their own brand on top of it by means of looking at how they could actually differentiate themselves from the rest of the others. Mobile app development services should follow this example to create their own low code mobile app which disrupts the market.

The best thing about this is that it inspires innovation. At present, the marketplace actually decides, and only the best applications rise to the top. Also, low code development easily allows developers to iterate much more quickly and can aim for higher more.

The Role of Artificial Intelligence (AI)

Artificial Intelligence is certainly making big waves in different businesses, and as this technology improves further, it will find its way in different other uncharted areas. Among those areas is the low code app development, where it comes in quite useful for a wide range of tasks and actions including the integration of various data sources or just making sense of an entire unstructured or semi-structured data.

Artificial Intelligence is quite great at analysing and conducting trial and error. Hence, it won’t be quite long until the usage of AI becomes quite a standard part of the low code app development. A mobile application development company can find ways to reduce the total amount of code that it is using through AI and flagging potential and possible improvements.

Conclusion

It is quite certain that low-code or no-code app development is the future of app development for one of the simplest reasons that it is quite easier as well as faster and efficiently uses time. It actually doesn’t matter whether Android app development services or iPhone app development services are on-board with this particular change or not. This is quite inevitable as this approach is the path of least resistance. Also, as the inherent demand for low code platforms keeps in growing, developers will certainly find themselves to adopt it.

It is quite a great news as it will push the developers of mobile application development services to become the best. Also, there won’t be any time to redoing it to create the same thing, or any room for sloppy code as well as lengthy development processes which makes the mobile apps redundant even before they are actually finished. Hence, low-code or no-code development will certainly lead the future of mobile app development, and mobile app developers certainly have to get on the bandwagon, one way or the other.