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Big Data and Artificial Intelligence in healthcare

Big data and AI in healthcare-s

Healthcare sectors have been growing for the last 10 years. But for the last couple of years, it is booming because of the COVID-19 pandemic. To tackle this problem, industries from all over the world are taking assistance from AI, Machine Learning, and Big Data technologies.

According to a survey conducted by Deloitte, 63% of the companies are using machine learning for business purposes. The market value of AI in healthcare will reach $6.6 billion in 2021 and is expected to reach more than it in 2022. There is a huge overlap between AI and Big Data in healthcare. The healthcare industry fetches Big Data and examines it for meaningful purposes such as AI and Machine Learning.

In this article, you will learn how Big Data and AI helps in the healthcare industry.

What is Big Data in healthcare?

Big Data in healthcare is a massive amount of data that is both structured and unstructured forms. Too much that we can’t handle in traditional ways, like storing them in hard drives. We can store this huge amount of data in clouds or customized memory storage.

Big Data development companies use this Big Data to analyze business and grow your company in the market. This is a helpful technique to find the deficiencies in your business and overcome them. In the healthcare sector, Big Data comprises patient medical records, patient treatment history, hospital records, exams results, medical machines data, and many more.

Big data in healthcare

Source: Unsplash

If the medical researchers and medical industry properly manage and analyze the data, they can prepare the medical industry for future pandemics.

Why is Big Data important in healthcare?

Collecting Big Data in healthcare is very important because it helps researchers and doctors to make well-researched decisions and treatments. For example, if a doctor analyzes a disease in a better way through Big Data, they can easily find the symptoms of that disease in a patient before it arises. If doctors treat diseases in earlier stages of the diseases, it can be cost-effective as well.

How Big Data improves patient outcomes

In the past, Big Data for medicine and healthcare industry was very expensive. But today, the technology has elevated and healthcare industries are collecting organizational data electronically via different resources. This data is converted into readable forms. From that data, healthcare professionals produce data-driven solutions for their patients and improve patient outcomes in different ways:

Big data for patient care

Types of healthcare data

Medical records are just one type of data in the healthcare IT solutions industry. According to the CDC report, approximately 883.7 million people visit office-based clinics annually in the United States. Over 85% office-based physicians use electronic medical record systems for collecting patient data. There are many types of data:

  • Medical records
  • Dental records
  • Surgical records
  • Behavioral data (for example, a patient’s diet)
  • Biometrics (for example, a patient’s blood pressure)
  • Living conditions.

Role of AI in healthcare

Here are a few benefits AI can provide the healthcare sector with:

  • Artificial intelligence helps people interact with the chatbot which works on the AI algorithms.
  • AI enables doctors to diagnose the patient with digital designs.
  • It also helps in identifying the drug factors in molecular structure by examining the image data. It also helps the radiologists to examine the image and diagnose the patients.
  • With the use of Big Data, you can personalize the patient’s data and treatment.

Ai telemedicine

Source: Unsplash

What is AI in healthcare?

AI in healthcare means that people train machines to perform medical tasks the same as humans do. Artificial Intelligence and Machine Learning expertise are used in the medical field to enhance the productivity of the clinics and manage the hospital systems. A prominent purpose of AI in the medical field is to produce medicine and diagnose patients with the latest technologies.

Artificial Intelligence helps in saving the lives of patients, enhancing the ways of diagnosis for doctors, and hospital management in less time and cost. Here are some ways to reduce errors in AI and save lives. After this section, you will also learn about the different companies that use AI to develop new medicines.

PathAI helps in cancer diagnosis

PathAI develops Machine Learning (ML) technology to help in cancer detection. The main purpose of PathAI is to reduce the errors in cancer diagnosis and develop some new technologies for medical treatment. It has worked with drug development companies such as Bill & Melinda Gates to grow the AI sector in healthcare.

Buoy Health for symptoms checking

Buoy Health is an AI-based symptom checker that uses some exceptional algorithms for patient treatment. It is like a chatbot. You can share your diseases with it and it will return to you with some diagnosis suggestions.

Enlitic for actionable insights

Enlitic is used to develop Machine Learning tools to help in radiology diagnosis. Many organizations use this Deep Learning platform to examine unstructured data sources like blood tests, images, and history of patients to give practitioners better results of patients’ real-time records.

AI for radiologists

Source: Unsplash

Freenome AI to detect cancer

Freenome uses AI to examine blood tests of patients and detect earlier cancer in the human body. It also uses new methodologies to develop new treatments for different types of cancer.

Developing new medicine with AI

The drug development industry is booming and increasing the costs of new medicines with the help of AI. It costs about $2.6 billion to put each drug through clinical trials and only 10% of the drugs are taken to the market. Pharmaceutical companies are taking notice of the efficiency, accuracy, and knowledge of AI. In 2007, one of the biggest AI breakthroughs came in drug development when a robot named Adam completed a research task on yeast.

In this section, we’ll elaborate on the companies that use AI to develop new medicines.

  • BioXcel Therapeutics is a company that uses AI to examine and produce new drugs and medicines in neurosciences and immuno-oncology. It helps find the new medicines and make some innovations in the existing medicines for the new patients.
  • BERG is a biotech platform that maps developed medicines to speed up the discovery of new ones. With traditional R&D, BERG can produce solid medicines that can cure serious diseases. They have discovered some rare links between different chemicals in the human body.
  • XTALPI has combined AI with quantum physics to predict the chemical properties of drug design and production. This company has claimed to predict the crystal structure of the molecules within the days.
  • Atomwise is a biotech industry that uses AI to develop medicines for fatal diseases. Atomwise makes some innovative solutions to take over diseases like Ebola in the future.

Key takeaways

Big Data and AI have influenced healthcare greatly. Big Data management helps healthcare institutions get the medical records, treatment records, history, and other data. This data enables practitioners to make better decisions for their patients. Big Data also assists different healthcare institutions and medical researchers to get solutions for pandemic situations in the future. AI uses this data and provides the medical industry with great robotic machines for diagnosing diseases.

In the past, doctors were unable to diagnose minor injuries in the head. But AI and Machine Learning make it easy for practitioners to get a better understanding of minor head injuries.

To put it simply, Big Data artificial intelligence made healthcare development companies more useful and advanced. Giant biotechnology companies are producing innovative drugs and medicines for patients. They are using AI technology to develop some medicines that can fight against rare and fatal diseases. All these companies have the primary goal of making robotic machines that can work automatically to reduce paperwork. Those machines decide based on their data and algorithms.

Author bio

Danie Bloom is a digital marketing expert. He has helped several brands grow from nothing to a successful name in the past few years. He believes smart work and business values go a long way for success. He is currently working with Invozone a multinational software development firm.

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