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Anahit Ghazaryan
Anahit Ghazaryan

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Artificial Intelligence and Machine Learning for Medicine Applications

Artificial Intelligence (AI) and Machine Learning (ML) have been transforming the healthcare industry since the early 2000s. AI was first described in 1950 but it was only in the 2000s that it could overcome its limitations and was empowered by deep learning. Given the rise of AI and ML in the healthcare sector, a lot of medicine applications have been built since the advent of 21 century. What do they look like and what are their prospects in 2022? Here is what you will learn.

  • Mobile apps in the healthcare industry
  • Why invest in mobile healthcare apps?
  • Machine Learning and Healthcare industry
  • Artificial Intelligence and Healthcare Industry

Mobile Apps in the Healthcare Industry

Let's see what mobile apps are and how they are used in the healthcare industry. Mobile apps are software programs. They are run on a computer or a mobile device. These apps perform various functions, like improved memory, less battery consumption, faster processing, etc.

How are they used in the healthcare industry? Have a look at some examples.

Let's take telemedicine apps. Patients can receive treatment and consultation from a doctor without leaving their house. A good example is eVisit. With this app, patients can meet their doctor virtually, search for medications, prescriptions, schedule a spot in a waiting room, etc. Naturally, patients save time and money by using this app.
Condition-based apps are another example. These apps notify a user about a particular health condition one should be aware of if they suffer from epilepsy, diabetes, cardiovascular disease, asthma, allergies, and even depression. An example is
Seizure Tracker that allows users to detect their seizures.
Other examples of mobile apps in health include meditation apps, fitness apps, diet and nutrition apps, doctor-on-demand apps, etc.

Why Invest in Mobile Healthcare Apps?

Today, in 2021, investing in mobile healthcare apps is a good idea. Why? There are several reasons for that.

  • Mobile healthcare apps are convenient for users. Patients can schedule appointments and meet their doctors at the comfort of their homes.
  • There is a rising demand for mobile healthcare apps. According to a Gallup survey Gallup survey, 45% of the US population has used a health or fitness app.
  • Experts predict growth by several billion in the sector. According to Statista, the global mHealth market size will grow up to $333 billion by 2025. According to healthcare market analysis by the Goldstein Market Intelligence, the growth in the global mHealth devices market is rated at a staggering 38.6% a year in the coming years.
  • Technologies like AI and ML boost this growth.
  • As an app owner, you can lower your budget by hiring development teams in Eastern Europe and Asia. For example, in Armenia, the cost is much lower totaling $50 on average as compared to the approximate annual rate of $107,000 in the USA.

Machine Learning and Healthcare Industry

Machine learning is a subset of artificial intelligence. It plays a key role in many health-related issues, including handling of patient data, treatment of diseases, and the development of new medical procedures.
Let's have a look at some machine learning applications.

Applications of machine learning

Identifying Diseases and Diagnosis: Today diseases that would be hard to diagnose otherwise are detected with the help of ML. An example is cancer that is hard to catch during the initial stages. IBM Watson Genomics is a good example of how ML can help in making a fast diagnosis. Another example is the detection of brain tumors and other brain-related diseases.

Drug manufacturing: An example is Project Hanover developed by Microsoft that is using ML-based technologies for cancer treatment and personalizing drug combinations for AML (Acute Myeloid Leukemia).

Clinical Trials: Before, a lot of time and resources were required to conduct research in clinical trials. Today ML-based predictive analytics is used to identify a pool of participants that can be used as data points for researchers to be tested.

Statistics on Healthcare and ML in 2021

  1. According to PolicyAdvice, the internet of things (IoT) is in a position to lower the operational and clinical inefficiencies costs by $100 billion per year.
  2. By 2020, medical data will double every 73 days, Forbes says.
  3. A survey by Deloitte says that out of 1,100 US companies, that were using Artificial Intelligence, 63% applied Machine Learning.
  4. Foresee medical says that Natural Language Processing is used to process data that was otherwise locked by 80%. In other words, the human brain could not process it in a structured way.
  5. By 2020, medical data will double every 73 days.

Key Factors

What are the key factors when we speak of machine learning today?

Validation: Yes, ML is trending and exciting, However, it requires robust validation to acquire the same rigor of solutions as we would have done for traditional technologies. Rigorous testing and research are needed to acquire valid solutions.

Priority of engineering over data science: Experts believe that engineers can pick up data science skills faster than data scientists can pick up engineering experience. Therefore, it is advised to employ engineers, especially in the production process.

Multiple algorithms: There is not one single algorithm for various situations. Therefore businesses require a diverse arsenal of algorithms to test against datasets.

Artificial Intelligence and Healthcare industry

What is artificial intelligence and how is it used in the healthcare industry? Simply put, AI is composed of complex algorithms with the help of which certain tasks are performed in an automated fashion. What kind of tasks can AI perform in the healthcare industry?

Let’s look at some applications.

Applications of Artificial Intelligence

The array of applications of AI in healthcare is wide. We will mention some of the popular cases.

Medical diagnostics: AI is to diagnose diseases. AI-supported software can be used to identify certain diseases in medical images such as MRIs. X-rays, and CT scans. AI is already used for cancer diagnosis by processing photos of skin lesions.

Drug development: Without AI drug development was time-consuming and expensive. These limitations were addressed by AI and it is now used to provide a quicker validation of the drug target and optimize the drug structure design. Have a look at some applications of AI in drug discovery.

Personalized medicine: AI can play a crucial role in personalized medicine. In other words, it can be used for tailoring health care to each person’s unique genetic makeup. We have launched an era where one-fit-for-all medicine is not sufficient anymore. Therefore big data-driven medicine is used for so-called individualized medicine, personalized medicine, or genomic medicine.

Patient monitoring and care: This is especially important at the time of pandemic when distance treatment was largely utilized. With AI-driven capability, providers can monitor thousands of patients at once. AI also helps to detect potential deterioration early, giving medical staff an advantage over Covid-19 and other critical conditions.

Statistics on Healthcare and AI in 2021

  1. According to Reports and Data, AI in healthcare will be worth 61,59 billion by 2027.
  2. Clinical trials were USD 620.5 million in 2018, Grand View Research says.
  3. Today, the healthcare industry in the US alone generates $1.668 trillion in revenue (Advertising Specialty Institute).
  4. According to the World Economic Forum, by 2025, there will be 97 million jobs that require ML specialists, process automation specialists, big data specialists, and more that will be adapted to machines and algorithms.

Key factors

So, what are the key factors when we speak of AI?

Capital: First, capital is running into the sector totaling $2.4 billion in 2015. Just in the first half of 2016, there were 200+ AI startups with a capital of over $1.5 billion.

New algorithms: Second, new algorithms, like Sentient, are developed that will attract new companies into the AI realm. These algorithms make the field accessible and a lot of companies can apply AI technology even if they would never think of it.

New chips: Finally, new chips are being developed that can empower AI. Examples are Alphabet, Qualcomm, and Nvidia.

Summing up

AI and ML are buzzwords today. They are penetrating many realms, including healthcare. We will witness new innovative solutions in the healthcare industry. The job market is going to adapt to the new environment with lots of engineers and data scientists in demand. The prospects are promising and there won't be any step back.

However, it seems that AI and ML will not replace clinicians on a large scale. Perhaps the only healthcare providers that will lose jobs will be the ones who refuse to work alongside the new technology.

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