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Artificial Intelligence (AI)

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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Artificial Intelligence (AI)

How to Build a Rewarding Career in Data Science?

We’ll explore the interesting world of data science, investigate its numerous applications, and offer you valuable tips on how to establish and grow a successful career in this exciting new sector.

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How to Build a Rewarding Career in Data Science

As the need for qualified data scientists grows, acquiring a Data Science Certification might lead to exciting new opportunities. Why Choose Data Science as a Career? This is a prevalent worry among students and recent grads interested in data science, predictive modelling, and AI/ML professions. If you are naturally strong with numbers, like solving riddles, and are naturally curious, consider a career in data science.

In this blog, we’ll explore the interesting world of data science, investigate its numerous applications, and offer you valuable tips on how to establish and grow a successful career in this exciting new sector.

1. Understanding Data Science: What Is It All About?

Data science is the process of gleaning valuable information from enormous databases. Understanding data patterns and making informed business decisions are aided by a combination of principles from computer science, statistics, and domain expertise. Businesses in every industry are racing to harness the power of data. This is where the services of trained data scientists with the appropriate tools may be invaluable.

2. Why Choose Data Science as a Career?

Before we go into how to get started in the industry, let’s discuss the advantages of a career in data science. Technological innovation is at the forefront of data science. From medicine to finance to retail to the arts, data science is having a profound impact. The potential to have an influence, solve problems, and make a difference in the world is great for those who work in this sector.

3. The Path to Becoming a Data Scientist

You’re obviously interested enough in data science to want to know how to get started in the field, so let’s talk about that. The road ahead may seem challenging, but with focus and strategy, you may make good progress.

a. Educational Foundation

A solid educational foundation is crucial for a successful career in the data science sector. Many data scientists get their start in the field by earning a bachelor’s degree in a quantitative field like Computer Science, Mathematics, or English. If you want to stand out in this competitive field, consider pursuing a master’s degree in data science or a related field or being certified in data science.

b. Develop Technical Skills

Data science requires a diverse range of abilities because of its technological nature. You should study Python and R since they are both widely used programming languages with practical applications in data analysis and machine learning. Use tools for displaying data, such as Matplotlib, and libraries for altering data, such as Pandas.

Understanding Object Lock A Shield for Data Immunity

c. Dive into Statistics and Machine Learning

Statistics act as the backbone of the data science field. Study the ins and outs of creating AI algorithms and statistical analysis. To get the most out of these strategies, try applying them to actual problems.

d. Build a Portfolio

The best way to display your ability is by practical practice. Take part in hackathons and open-source projects. A portfolio is an excellent way to demonstrate your skills and passion.

e. Network and Collaborate

Building your network in the data science community might open doors to paid and unpaid internships. Learn from industry experts by participating in seminars and online discussion groups. The results of collaborative activities are often shared knowledge and shared responsibility for tasks.

f. Stay Updated

Data science is a dynamic field that’s constantly evolving. Be informed about the latest advances in the area. Continuous learning is essential for keeping one’s competitive edge in the workplace.

4. Job Opportunities in Data Science

If you have a varied set of talents and a data science certification, you’ll be eligible for a variety of opportunities in the data science ecosystem.

  1. Data Analyst: Determine actionable insights from data via analysis.
  2. Machine Learning Engineer: Machine learning engineers develop and implement intelligent software that can teach itself.
  3. Data Engineer: Manage data pipelines and infrastructure.
  4. AI Research Scientist: Work as a scientist who focuses on artificial intelligence and does research to better the field.
  5. Data Scientist: Data Scientists use their knowledge and expertise in specialized fields to solve complex problems.

5. Final Thoughts

Data science may be a fulfilling and intellectually stimulating career. Start a productive career by investing in your education, technical skills, and experience. Data science certification might help you succeed professionally. Data science may be appropriate for you if you love data and want to change the world. If you study hard and work hard in this field, you can influence global enterprises.

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