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How AI and Machine Learning are Revolutionizing Healthcare Industry?

Among all the industries set to be impacted by artificial intelligence (AI) and machine learning (ML), the healthcare sector stands to benefit the most.

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AI and Machine Learning are Revolutionizing Healthcare Industry

Among all the industries set to be impacted by artificial intelligence (AI) and machine learning (ML), the healthcare sector stands to benefit the most.

In fact, in a report made by a consulting firm, Frost & Sullivan, it was stated that the healthcare AI market is estimated to experience a compound annual growth rate of 40% through 2021.

It is mainly because technologies like Data Science, Machine Learning, and AI are capable of improving healthcare outcomes by 30 to 40% while simultaneously reducing the costs of treatment in half.

Health AI Market Size
(Image Source)

As per Accenture’s reports, AI applications can create yearly savings of $150 billion by 2026 for US healthcare.

These innovative technologies are typically used in healthcare to handle the complexity and growth of medical data. These AI solutions are used in healthcare to handle the complexity and growth of medical data. The benefits offered by AI and machine learning include automated disease diagnosis, maintaining a healthy lifestyle, personalization of treatment pathways, helping patients in real-time, advancement in treatments, and cutting costs. And these are only a few.

Let’s take a look at how AI and machine learning impact the healthcare industry.

1. Improved Automated Disease Diagnosis

The medical industry is already using AI to improve medical diagnosis. For instance, the Beijing-based artificial intelligence high-tech company is using AI-aided medical image diagnosis to improve reading CT scans and x-rays. Read more about Beijing-based Inversion here.

Stanford University researchers have created an AI algorithm that can spot and diagnose skin cancer. Also, Google has created an AI program to detect metastasis using high-level image recognition. The company claims 99% accuracy in metastatic breast cancer detection.

Moreover, since AI can analyze large volumes of data, it can detect disease and helps with clinical decisions.

2. Maintaining Wellness

Using AI in consumer health applications is helping people stay healthy. People don’t need a doctor as often as they used to before. Some apps encourage healthier behavior in individuals and assist in proactively managing a healthy lifestyle.

For instance, apps like MyFitnessPal can help you to track your diet programs through a database that offers nutrition information for more than 5 million foods.

AI Maintaining Wellness
Image Source

Furthermore, AI helps healthcare professionals to understand the everyday patterns and needs of patients better. They are also able to provide better feedback, direction, and support for staying healthy.

3. Personalizing Treatment

Not all patients respond to drugs and treatment schedules in the same manner, so personalized treatment is very beneficial. However, it is difficult to identify which factors should affect the choice of treatment. This is where machine learning comes in.

Machine Learning can simplify complicated statistical work. It can help determine which characteristics indicate that a patient or a group of patients will have an appropriate response to a specific treatment.

Machine learning does this by cross-referencing similar patients and comparing their treatments and outcomes, making it much easier for doctors to design the right treatment plan.

Also, as per a new study by the Cleveland Clinic, artificial intelligence and machine learning networks can personalize radiation therapy for lung cancer. AI can learn from imaging and electronic health records. It can predict if an individual patient could fail radiation treatments, thus individualizing radiotherapy treatments for patients with lung cancers.

Yet in another study made by the Institute of Cancer Research, scientists with the help of artificial intelligence have spotted patterns in breast cancer and exposed five new types of the disease each matched to different personalized treatments.

4. Helping Patients in Real-Time

Innovative and advanced healthcare Bots today can learn and mimic human conversations, detect emotions that allow empathetic engagement with patients, incorporate Natural Language Processing, sentiment analysis, and concept mining into chat scripts, and recognize the intricate image to analyze photos, handwritten notes, and barcodes. It is not only about sending messages.

However, the primary reason why healthcare bots exist is to help patients quickly and in real-time simply by sending a message, making it great for emergencies.

Helping Patients in Real-Time Using AI
Image Source

It can even assist patients in managing medications by offering information on types of medications and recommended doses.

For instance, the Microsoft Healthcare Bot service helps healthcare organizations to build and set up an AI-powered, compliant, conversational healthcare experience.

It is suitable for healthcare providers, pharmaceutical companies, telemedicine providers, and health insurers. The Health Bot Service contains built-in scenarios including a symptom checker; general information about conditions, symptoms, causes, complications, and more; finding doctor type; health plan inquiries; finding providers, and scheduling appointments.

5. Advancement in Treatments

With the help of AI, new treatment methods are being generated and introduced, including robotic surgery. In 2018, over 5,000 surgical robots were used in over 1 million procedures across the world. And the procedures encompassed orthopedics, urology, gynecology, neurology, otolaryngology, rectal and colon, dental implants, hair transplants, and more.

AI is also used for diabetes management. And a Boston-based Bionic Pancreas that uses machine learning has been introduced to aid adults and children with type 1 diabetes. Read more about the device here.

Potential Cost Savings in AI Applications
Image Source

Furthermore, wound healing by printing skin cells, 3D printing of human body parts, and blood vessel reproduction are all made possible through AI.

6. Reduce Costs

Health Policy Brief noticed that in 2012, $300 billion was being spent on pointless healthcare costs. The costs were associated with fraud, waste, and abuse; absence of or low value-added work; and no collaboration between stakeholders.

As per Frost & Sullivan reports, AI can improve outcomes by 30- 40% and reduce the cost of treatment by as much as 50%. When there is an improvement in precision and efficiency, there will be fewer human errors. There will be a decrease in doctor visits. Moreover, doctors can obtain information from data for patients who are at risk of certain diseases to avert hospital readmissions.

If you look at the bigger scenario, as per Healthcare IT news, potential cost savings in AI applications in billions of dollars are shown below:

Machine learning and AI have the potential to drastically change the cost and quality curve in healthcare.

7. Winding Up

AI is the game-changer in the healthcare industry. It has changed the role of doctors and even the role of patients. It has transformed how diseases are detected and diagnosed, how treatments are offered, helped discover new treatment methods, and saves time and cost as well.

No doubt, challenges are being faced by AI and machine learning in the healthcare industry, but it is ever-growing and expanding. It has become an inherent part of medical care in many parts of the world.

Helpful Resources:

1. 16 Best (free) AMP – (Accelerated Mobile Pages) WordPress Plugins

2. Top 10 Artificial Intelligence (AI) App Development Trends

3. Artificial Intelligence And Its Demands To The Programmers

4. Artificial intelligence (AI): Friend or Foe to Future Designers?

5. How Augmented Reality Will Change The Future Of the Design Industry

Lucy Manole is a creative content writer and strategist at Right Mix Marketing Blog. She specializes in writing about digital marketing, cybersecurity, technology, entrepreneurship and education. When she is not writing or editing, she spends time reading books, cooking, and traveling.

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A Guide To Using AI for Knowledge Management

Using AI for knowledge management and to transform massive data pools into actionable insights is not just beneficial; it’s becoming a necessity to stay competitive.

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In the digital era, the fusion of AI technology with knowledge management is revolutionizing the way organizations manage and exploit their informational assets. Using AI for knowledge management and to transform massive data pools into actionable insights is not just beneficial; it’s becoming a necessity to stay competitive. Keep reading to unlock the full potential of AI-driven knowledge management.

1. The Intersection of AI and Knowledge Management: A Synergy Explained

Knowledge management traditionally involves capturing, organizing, and distributing knowledge across an organization. When AI steps into this territory, the potential for enhanced efficiency and decision-making emerges. AI algorithms can sort through and analyze data at a rate no human can match, revealing patterns and insights that can be critical for strategic planning. This melding of AI with knowledge management practices is a modern alchemy, creating an invaluable resource.

One of the most significant benefits of integrating AI into knowledge management is the automation of data processing. AI systems can continuously learn from new data, refining their algorithms and providing even richer insights over time. Moving from static data repositories to dynamic knowledge hubs, businesses are now armed with constantly evolving intelligence. This represents a profound shift from data being a static historical record to a dynamic, predictive tool for decision-making.

Using AI for Knowledge Management is a top solution

Customization is another strong suit of AI in this space. Rather than one-size-fits-all information resources, AI can personalize knowledge dissemination to the needs of each employee. The focus moves beyond mere information access to ensuring the right knowledge reaches the right person at the right time.

2. Implementing AI in Your Knowledge Management Strategy

Transitioning to an AI-driven knowledge management system begins with identifying the scope and objectives of knowledge needed. Organizations must be clear about the kind of knowledge that is most valuable and how AI can aid in its cultivation and dissemination.

Following initial evaluations, the selection of appropriate AI tools and technologies becomes the next crucial step. There are various AI solutions designed for specific knowledge management tasks, from natural language processing for content analysis to machine learning models that predict trends and behaviors.

Integrating AI requires a cultural shift within the organization. Employee buy-in is crucial, and it is important to address any concerns about job displacement head-on. Training and educating the workforce on the benefits and use of AI systems can facilitate smoother adoption, ensuring everyone understands the role of AI as a partner, not a replacement, in the knowledge ecosystem.

3. The Impact of AI on Knowledge Retention and Dissemination

An AI chip sits in a computer

The true value of AI in knowledge management is often most visible when assessing knowledge retention and dissemination within the organization. AI-driven systems can significantly enhance the ability to capture institutional knowledge, store it and make it available in engaging, interactive formats that increase retention.

Analytics are also central to measuring the impact of AI on knowledge management. By evaluating these metrics, businesses can see whether the knowledge is being leveraged effectively, which areas may need more focus, and where improvements can be made.

Furthermore, AI can be a boon for training and development programs. By adapting to the learning pace and style of individual employees, AI can deliver personalized training recommendations and content, leading to more effective learning outcomes.

Altogether, AI is transforming the realm of knowledge management with its capacity to automate, personalize, and revolutionize how information is processed and utilized. Challenges notwithstanding, the rewards of integrating AI into knowledge management strategies are profound, paving the way for smarter.

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