Anton Chekov practiced medicine in a time when diseases are just phenotypes. Today, the healthcare system has progressed significantly, and big data has the biggest impact on it. Data-driven thinking and methods have now opened the doors for personalized healthcare systems.

 Tailored experiences have become the standard in today’s environment. From the music we listen to the TV episodes we watch to the purchases we make, these are frequent suggestions based on data acquired about us, such as our purchasing and streaming histories.

The goal of a personalized healthcare system is to enable patients to have a personalized assessment of their health including a list of lifestyles change recommendations based on predicted health risks.

We haven’t completely reached the realm of personalized medicine yet, but it’s a few years ahead.AI powered Big data analytic tools will be the driving force for achieving this. IDC research predicts the global data sphere will grow to 175 zettabytes by 2025. Medical practices leverage the power of machine learning techniques to identify trends, patterns, and anomalies in the data to help experts make better diagnoses and treatment decisions. Complete personalized healthcare will only be possible when clinicians can understand which gene mutations or differences may cause specific illnesses (Since each one of us has a unique variation of the human genome)

To accomplish the comprehensive perspective of each patient, we must collect data from health records and lifestyle habits from many sources regularly and combine it into a unified perspective. This data is critical for understanding and analyzing each patient’s demands, which may be used to guide both medication development and the sort of treatment that a patient receives.

AI and machine learning help pharmaceutical companies gather, store, and analyze massive data sets easier than traditional procedures. It enables quick research based on genetic variation data from different patients and develops personalized medicines.

In a NutShell

In an ideal world, we would like to eliminate diseases. We may introduce preventative measures and therapies far earlier, sometimes even before a patient begins to exhibit symptoms, if we have a greater understanding of why, how, and in which people’s illnesses develop. Personalized medicine has the potential to enhance and possibly save many people’s lives, and artificial intelligence and machine learning will be the driving forces behind future discoveries.

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Global Artificial Intelligence Summit & Awards

If you or your organization is building cutting-edge AI solutions to adapt to a world driven by technology, Please nominate yourself/or your company for GAISA AWARDS 2022.

Please follow the below-given link to nominate:https://gaisa.in/award

All further details regarding the event will be updated on the official website of Gaisa 2022. Please Visit: https://gaisa.in/

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But is India ready to take advantage of the tremendous prospects that AI offers? Find out by reading on.

India trails on important AI development metrics despite having a talent pool that is tech-savvy, well-regarded colleges, high levels of entrepreneurship, and powerful enterprises. The odds are against us. Although it is still the most competitive in South Asia, the nation lagged behind several other G20 nations in AI. This is true despite the fact that Indian businesses are using AI technology more broadly, the nation has invested in technological infrastructure, and its people are becoming more tech-savvy.

The opportunity for AI driven growth

AI has the power to transform industries for large corporations and sectors by accelerating growth and profitability. Consider manufacturing. Artificial intelligence (AI)-powered systems, whose capacity to learn, adapt, and grow over time may eliminate defective machinery and inactive equipment, might result in a 39 percent rise in the sector’s share of profits.

AI may be a tool for startups and entrepreneurs to compete with much larger incumbents.

AI has the potential to save lives and increase public safety for society.

Stepping up to the opportunity

According to our research, thriving AI ecosystems are supported by five different types of institutions: universities, huge companies, startups, policymakers, and multi-stakeholder alliances. The relative importance of these five changes from market to market and is influenced in part by the level of development of certain sectors and the political climate of each nation.

India’s AI stakeholders should take into account the following five suggestions to comprehend how to promote growth and innovation while preserving consumer rights and ethical considerations:

• Forge a national AI plan and multi-stakeholder partnerships in key sectors
• Strengthen India’s AI research and development ecosystem, including through better international cooperation
• Create a workforce of the AI future, fostering inclusive workforce models
• Enable and broaden access to data
• Embrace smart regulation to safeguard responsible AI

AI promises to fill the gap at a time when India is attempting to reignite productivity and growth. AI will create new economic possibilities that would not have been possible without its complete and prudent application. Create “people first” policies and commercial strategies that are focused on utilising AI to enhance and extend people’s capabilities for the benefit of humanity as the guiding philosophy.

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This AI plateau is happening beneath the surface, smartening our existing technology and unleashing the power of all the data that organizations collect. That is to say, advances in machine learning (ML), computer vision, deep learning, and natural language processing (NLP) have made incorporating an AI algorithm layer into your software or cloud platform easier than ever.

Depending on your organization’s needs and the business intelligence (BI) insights generated from the data you collect, practical AI applications for organizations might develop in a variety of ways. Businesses can utilize AI for anything from mining social data to increasing consumer engagement in customer relationship management (CRM) to optimizing logistics and efficiency in asset tracking and management.

How to integrate AI into your business

Take the time to understand what modern artificial intelligence can do. You should also educate yourself on the core concepts of AI by using the various online materials and tools accessible.

Determine the Issues You Want AI to Solve

After you’ve mastered the fundamentals, the next step for any company is to begin experimenting with new ideas. Consider incorporating AI capabilities into your current products and services. More importantly, your organization should have clear use cases in mind where AI may solve business problems or provide provable value.

Prioritize Concrete Value

Next, evaluate the potential business and financial value of the various AI implementations you’ve identified.

Recognize the Internal Capability Deficit

There is a significant disparity between what you want to accomplish and what you have the organizational capacity to accomplish within a particular time frame. Before entering into a full-fledged AI implementation, a company should understand what it is and is not capable of in terms of technology and business processes.

Recruit Experts and Launch a Pilot Project

Once your organization and technology are in place, it is time to begin building and integrating. The most important things to remember here are to start small, set project goals, and, most importantly, be conscious of what you do and don’t know about AI. Bringing in outside specialists or AI consultants can be extremely beneficial in this situation.

The post HOW TO ADOPT AI IN YOUR BUSINESS appeared first on AICRA.

2. New capabilities and business model expansion-
deploy data and analytics into the enterprise, it opens up new opportunities for businesses to participate in different areas. For example, autonomous vehicle companies, with the reams of data they’re collecting, could identify new revenue streams related to insurance, while an insurance company could apply AI to its vast data stores to get into fleet management.

3. Improved monitoring-
AI’s capacity to take in and process massive amounts of data in real-time means organizations can implement near-instantaneous monitoring capabilities that can alert them to issues, recommend action, and, in some cases, even initiate a response.
For example, AI can take the information gathered by devices on factory equipment to identify problems in those machines as well as predict what maintenance will be needed when thereby preventing costly and disruptive breakdowns, as well as the cost of maintenance work, performed because it’s scheduled rather than because it’s needed.

4. Better quality and reduction of human error-
Organizations can expect a reduction of errors as well as stronger adherence to established standards when they add AI technologies to processes. When AI and machine learning are integrated with technology like RPA, which automates repetitive, rules-based tasks, the combination not only speeds up processes and reduces errors but can also be trained to improve upon itself and take on broader tasks.

5. Minimize operational costs-
Errors can not only postpone the release date of your product, for instance — they can also cost your company a lot. However, you can use AI to minimize the number of errors and improve the efficiency of your company. Here is an example for you.
Most of the company solution is allows plant managers to make better use of the sensor data they already have.
Predict asset failures with enough lead time to take corrective actions before the equipment has a chance to break down while leaving assets that do not need maintenance to continue running.

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