Description:ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN
HEALTHCARE APPLICATION
BACKGROUND
[0001] The present disclosure relates use of Artificial Intelligence and Machine learning in Health care application.

[0002] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art

[0003] Artificial Intelligence (AI) is a wide-ranging branch of computer science concerned with building a smart machine capable of performing tasks that typically require human intelligence. In general, the Al system work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about the future state.

[0004] Machine learning is a tool used in health care to help medical professionals care for patients and manage clinical data. It is an application of artificial intelligence, which involves programming computers to mimic how people think and learn.

[0005] Machine Learning has altered the healthcare system by enabling artificial intelligence to be used in medical diagnosis and treatment. Machine learning algorithms can quickly process large amounts of clinical documentation, identify patterns and make predictions about medical outcomes with greater accuracy than ever before.
 
[0006] The increasingly growing number of applications of machine learning in healthcare allows us to glimpse at a future where data, analysis, and innovation work hand-in-hand to help countless patients without them ever realizing it. Soon, it will be quite common to find ML-based applications embedded with real-time patient data available from different healthcare systems in multiple countries

DETAILED DESCRIPTION
[0007] Primary object of the invention is to use of Artificial Intelligence and Machine learning in Health care application.
[0008] Artificial intelligence (AI) and related technologies are increasingly prevalent in business and society, and are beginning to be applied to healthcare. These technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer and pharmaceutical organizations.
[0009] This study suggesting that AI can perform as well as or better than humans at key healthcare tasks, such as diagnosing disease. Today, algorithms are already outperforming radiologists at spotting malignant tumors, and guiding researchers in how to construct cohorts for costly clinical trials.
[0010] In healthcare, the most common application of traditional machine learning is precision medicine – predicting what treatment protocols are likely to succeed on a patient based on various patient attributes and the treatment context. The great majority of machine learning and precision medicine applications require a training dataset for which the outcome variable.
[0011] Heart disease is a primary killer of human beings around the world; it’s no surprise that effort and focus from many AI innovators is on heart disease diagnosis and prevention. The current process to determine an individual’s risk factors for a heart attack are age, blood pressure and more. However, this is really a simplistic approach and doesn’t take into account medications someone might be on, the health of the patient’s other biological systems and other factors that could increase odds of a heart ailment.
[0012] Another area where AI can impact healthcare is in the way information is gathered and shared about disease treatment. Artificial intelligence and machine learning in healthcare will continue to get better and impact disease prevention and diagnosis, extract more meaning from data across various clinical trials, help develop customized drugs based on an individual’s unique DNA and inform treatment options among other things.
[0013] One of the important of machine learning applications in healthcare is the identification and diagnosis of diseases and ailments which are otherwise considered hard-to-diagnose. This can include anything from cancers which are tough to catch during the initial stages, to other genetic diseases
 
, Claims:I/We Claim:

1. Use of Artificial Intelligence and machine learning in healthcare application in terms of data gathering, future prediction and reliable treatment;

2. Use of Artificial Intelligence and machine learning in future prediction as we claim in claim 1; diseases prediction, identification and diagnosis the same at earlier stage;

3. Data gathering as we claim in claim 1; use for research purpose, improving treatment outcomes and reducing cost. oriented to the development of enterprises and current technology;