Artificial intelligence in healthcare is poised to deploy trillion gigabytes of medical data for generating valuable insights beyond human intelligence. Business Insider Intelligence report suggests that AI spending in healthcare is expected to...
Artificial intelligence in healthcare is poised to deploy trillion gigabytes of medical data for generating valuable insights beyond human intelligence. Business Insider Intelligence report suggests that AI spending in healthcare is expected to grow at 48% between 2017 and 2023. AI-powered machine learning models are improving the diagnostic abilities of doctors and ensuring effective deliverability of treatment with dynamic machine learning models.
This blog post explores how healthcare providers are using AI development services to mitigate medical challenges efficiently.
Predicting Health RisksMachines are beginning to surpass human foresightedness with advanced algorithms. Under AI’s vast umbrella, machine learning algorithms are capable of sifting through unstructured data and identifying patterns to generate relevant insights.
Early diagnosis of health risks, diseases, and rare conditions is a major challenge for medical professionals. However, with the advent of AI’s predictive analytics techniques, doctors are able to gauge the probability of certain health risks. The underlying ML algorithms of predictive engines use patient’s Electronic Data Record (EHR) and medical reports to-
a) Predict risk of heart attacks at least 4 to 5 in advance
b) Predict death risk caused by persistent chronic diseases including diabetes and cancer
c) Prevent infectious diseases by predicting epidemic disease dynamics
Tests and studies suggest that AI can accurately predict a multitude of health-related risks and diseases for timely prevention. In addition, data scientists are working on ML models that can not only diagnose diseases but also suggest possible treatments.
How does Oodles use Artificial Intelligence in healthcare to strengthen diagnosis?We, at Oodles AI, practice data-driven predictive analysis powered by machine learning algorithms for accurate and timely prediction of health conditions. We are adept at training ML models with Electronic Health Records (EHR), 2D and 3D images to assist health institutes with automated insights.
Recently, our AI team has developed a Diabetic Prediction System using Python and machine learning libraries such as Scikit-learn and Flask. The model requires structured data inputs such as Plasma Glucose, Tricep Thickness, Blood Pressure, and other medical details to draw diabetic predictions.
predictive analytics healthcare ai
The USP of this model is that it does not require any intervention of a physician to measure a person’s diabetes. The system supports a simplified interface that enables common individuals to test diabetes in a simple and accurate manner.
Improving Remote Patient Monitoring with Conversational AIInteractions between patients and medical practitioners are a vital source of medical diagnosis and symptom analysis. However, the unavailability of proper medical facilities in remote areas drastically affects public health leading to an outbreak of deadly diseases.
The conversational potential of Artificial intelligence in healthcare is poised to combat the challenges of remote diagnostics with virtual assistants. Voice and text-based chatbots and virtual assistants represent a user-friendly medium to discuss health issues in detail. The combination of computer vision and natural language processing (NLP) capabilities of AI empowers chatbots for-
a) Remote assessment of symptoms and drug prescriptions
b) Preliminary diagnosis
c) Right health plan selection
d) Administrative workflow assistance
RASA, an open-source chatbot development framework, supports remote patient monitoring with machine learning-enabled virtual assistants.
rasa chatbot for healthcare
The chatbot facilitates medical consultation for surgeries, scheduling of appointments, collection of patient feedback, onboarding new patients, and more.
How does Oodles AI accelerate medical diagnosis with Conversational AI?The AI team at Oodles provides timely healthcare assistance to patients across borders with reduced administrative costs. We ensure the responsible use of critical medical data for human-like medical consultation along with the following benefits-
a) We have hands-on experience in using the RASA framework to build medical virtual assistants that assist patients with precise medical prescriptions. Our team uses historical data to train the chatbot’s algorithms for accurate matching of multiple diseases and timely solutions.
artificial intelligence in healthcare with RASA
RASA bot assistant built by Oodles AI in action.
b) Our NLP services are effective at replacing time-taking manual methods to suspect adverse drug reactions (ADR) from databases and medical reports. Our deep neural network capabilities can save up to a million serious injuries and deaths due to unreported or ill-reported ADRs.
Talk to our AI development team to know more about our Artificial Intelligence Services.
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.
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.
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