The advent of the healthcare application development industry has brought so much change in the traditional healthcare industry that spending large sums and waiting in long queues is now limited to mobile devices.

In today's medical landscape, the picture has transformed. Now-a-days, when a body starts behaving abnormally, a smartphone healthcare app operated by a private or public health organization will flag it and assist with the first step: i.e life. A push to make healthy or a direct diagnosis of one-off issues such as sprains, heartburn or the flu.

When required, it also provides referral to human expert or general practitioner, saving a visit of the patient to the hospital.

The medical data of the patient then stored, integrated and monitored through machine-learning algorithms in the cloud, that enables the doctors to choose the trends as well as interaction at a niche and helps in predicting and preventing disease even before it happens.

Although yet a very straight forward approach, three disruptive technologies have already revolutionizing healthcare industry: Artificial Intelligence, Virtual Reality, Blockchain and Wearable.

In this blog, we will see first of them, i.e AI, giving an idea about the working of the healthcare industry which will go to get shape in future. Looking towards the ways the technology is transforming and why it is crucial time for you to implement machine learning in your healthcare mobile apps for marking the space in industry's future:

Let's start:

1. AI in Healthcare:
AI in mixed medicine and healthcare with mobile application development is helping to better organize treatment plans and patient paths, while providing physicians with all the input and data that can actually come to an informed decision.

Artificial Intelligence has already helped the healthcare industry revolutionize the domain from the design of the treatment process by helping to improve repeat jobs for better drug management and drug manufacturing. Found in various applications, this is all just the beginning.

2. Medical Record Mining
The most common use of AI in healthcare is data management. This is why the majority of AI based mHealth apps currently practiced in the industry provide this feature. Various healthcare organizations are going with mobile app development companies to develop robust mHealth app.

Collecting, assembling, normalizing offspring and then locating offspring is the primary stage of changing the current health system - a process that helps AI to get into and follow daily behavior.

Recently, Google launched the Google DeepMind Health Program, which is now being used to provide more efficient and faster health-related services for healthcare data.

3. Treatment plans designs:
IBM Watson recently introduced a scheme for oncologists, which offers physicians many treatment-based treatment options. The program has the ability to analyze the definition and context of all structured and unstructured data in clinical notes and to provide critical reports for the selection process to finalize the treatment process.

While IBM Watson for oncology is a high-level application of AI technology, there are mobile apps that analyze data: analyze reports and help define the treatment pathway.

4. Repetitive Jobs Assistance:
Healthcare is heading towards cognitive world assistants who come with all range of reasoning, analytical abilities, and medical knowledge. IBM has recently launched an algorithm, Medical Sieve, that is qualified to support cardiology and radiology decisions.

The cognitive health assistant, as coined as the medical strainer, then analyzes radiology images to detect problems faster with greater reliability.

The medical Sieve is just one example. There are other techniques, such as analytic, that aim to provide deeper diagnosis and improve patient outcomes with medical data for advance diagnosis.

5. Healthcare System Analysis:
With more and more healthcare invoices being digital, every data based to doctors, treatment and medical establishment can be easily obtained. On data mining, hospitals can generate reports on the mistakes they are making consistently in the treatment of a certain type of condition, so as to avoid unnecessary hospitalization of patients when needed.

Netherlands Company Jogprisma is analyzing invoices shared by public hospitals and using IBM Watson technology to complete the data collected.

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Author's Bio: 

Vivek Ghai has over 18 years of experience in software services industry. He is the founder of a software company specializing in web and mobile application development. He has hands-on experience in operations, digital marketing and business development in the technology industry. He advises start-ups and also is a technical co-founder for few of them.