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The Impact of AI on Healthcare Apps

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The use of AI healthcare apps has been on the rise and will continue growing — almost half of the healthcare companies globally are willing to integrate AI by 2025. And it is reasonable: artificial intelligence, machine learning, deep learning, natural language processing, robotics, and other associated technologies have been reshaping the industry. 

From streamlined drug discovery to robotics-assisted surgeries, AI has brought unique opportunities to improve the quality of our lives through enhanced medical processes and a more thorough approach to patient care. Across all stages and areas of healthcare services, we benefit from integrating artificial intelligence into mHealth apps.

AI-Powered Medical Technology Market

Artificial intelligence has significantly enhanced healthcare service providers’ and researchers’ possibilities. Most importantly, AI brings a massive acceleration in the speed and quality of process completion due to automation. 

And this transformation cannot be left unnoticed. Over the recent several years, the size of AI-enabled health apps has grown 11 times, from $600M in 2014 to $6.6B in 2021. Naturally, this is only the beginning of the growth — AI services development in the healthcare sector provides immense opportunities for all parties.

AI healthcare apps market size 2014-2021
Figure 1. Health AI market size 2014-2021

So how exactly is artificial intelligence transforming the capabilities of e-health apps? Let’s discuss the applications of AI in healthcare software.

Uses of AI in mHealth Apps

AI services development in healthcare ranges from research and treatment to patient care. The automation that AI and associated technologies provide allows for better outcomes over a shorter period without neglecting the quality of the results, regardless of the area or process.

Applications of artificial intelligence in healthcare
Figure 2. Uses of AI in healthcare

Here are some use cases for AI in healthcare that have been transforming mHealth apps and bringing new opportunities to the industry.

1. Faster Drug Discovery

AI and machine learning algorithms have helped speed up the process of drug discovery. When traditionally approaching drug discovery and development, the process can take up to 12 years. But with AI technologies, it is possible to develop a new drug several times faster.

Drug discovery & development process
Figure 3. Drug discovery & development process

In particular, AI algorithms are helpful at all stages of the process and assist humans with decision-making based on loads of data analyzed. That allows implementing something called a “fail fast” approach. It implies identifying and eliminating potential failures that can occur later in the process, such as when it comes to testing the drug, through analyzing various scenarios at earlier stages of drug development. 

While developing certain medications in the shortest possible time frame may not always be crucial, the global COVID-19 pandemic has shown us a different scenario. At its beginning, the rapid development of vaccines was a must to prevent the virus from spreading. 

With this, AI facilitates and streamlines drug discovery, which allows combating diseases faster and reducing their drastic impact on us individually or as humankind.

2. Early Disease Detection

Artificial intelligence enables medical specialists to spot signs of severe conditions early on. This way, the diseases are still possible to be treated or can be stopped from worsening with preventative measures. That can be applied to various health areas — from skincare to cancer. 

For example, images of one’s face taken with a dedicated device in a dermatologist’s room can be further analyzed by AI tools to determine the condition of the person’s skin. The software can identify the problem areas from the scan based on information from other people’s images. Then, AI healthcare apps predict the development of skin issues based on the current condition, which allows the dermatologist to prescribe preventative skincare.

Another application of AI for early disease detection is cancer. For instance, one tool can analyze women’s mammograms several times faster and with 99% accuracy. That, in turn, reduces the need for biopsy, allowing the medical specialist to make conclusions about the patient’s health conditions in an effective, safe and quick way.

AI-powered early disease detection & prediction
Figure 4. AI-powered early disease detection & prediction

Then, artificial intelligence in healthcare tools can detect early signs of dementia through brain image analysis and speech recognition. After patients go through a short speaking test, the tool assesses the complexity of their speech, the use and length of pauses, and the word choice to identify changes in their cognitive abilities as early as 20 years before the symptoms occur

Not to mention, wearables bring early disease detection to a new level. People with heart conditions benefit from AI-aided analysis of the data their smartwatches collect, notifying them or the doctor directly in case of any complications or unhealthy patterns in the performance of their heart, eventually saving people’s lives. This way, they can take measures before they reach a life-threatening episode due to the condition.

3. More Profound Medical Diagnostics

Electronic Health Records (EHRs), to which many clinics globally have already transitioned, provide access to priceless patient health data. That allows AI to identify the causes and effects between symptoms and diseases. Especially tools like IBM’s Watson Health and Google’s DeepMind Health provide huge data loads for AI to learn from. Then, based on the data, the tool can provide conclusions for patient diagnostics.

In particular, AI-powered diagnostics enhance the speed and quality of test taking and examination based on image analysis. For example, recognition software can identify phenotypes associated with rare diseases in a patient and detect cancerous tissues early on.

So while AI technology imitates the human brain in decision-making, it can also analyze loads of patient health data that are significantly larger than those a human can handle. Eventually, this translates into faster and more accurate diagnostics with no human error while applying to many healthcare directions.

4. Chatbots’ Assistance in e-Health Apps

The integration of chatbots into mHealth apps has changed the user experience significantly. Because chatbots allow patients to receive healthcare services quickly and effectively from the comfort of their homes, this asset has increased customer satisfaction drastically. The research shows that 80% of chatbot users report a positive experience, and 69% prefer chatbots over human agents. 

So how are the chatbots helping patients? Well, in multiple ways.

For instance, a patient can log the symptoms in the AI healthcare apps so that the AI-driven chatbot can analyze them and, using natural language processing (NLP), provide recommendations on the measures the patient can take on their own or offer to visit a doctor. 

Thus, chatbots have become an intermediate step between the patient and the doctor when people need medical assistance. This way, chatbots handle patients with easier conditions, preventing overbooking without leaving any patients behind. 

How an AI chatbot works in healthcare
Figure 5. How an AI chatbot works in healthcare

Then, AI chatbots collect helpful information on the patient’s concerns regarding their health. So if they go to the doctor, the latter already has all the needed information. That saves time on the general examination and allows a more profound analysis during the visit and tracking of disease progression.

Therefore, chatbots provide attentive patient care at the quality level of human-human interaction while automating the process, making it faster and more accurate.

5. Improved Treatment Experience & Outcomes

Thanks to chatbots, easily accessible EHRs, and various mHealth capabilities, artificial intelligence has elevated all stages of healthcare service provision, including treatment. Both doctors and patients can access a person’s medical history and treatment journey logs within seconds from different devices and locations. They can also receive AI-informed recommendations on treatment decisions. 

Not to mention, exchanging information between departments of a healthcare facility is quick and straightforward. That allows for effective collaboration driven by AI services development.

Tools driven by artificial intelligence in healthcare can also determine the best time for the patient to take medication or undergo medical procedures to achieve the best outcomes. It is beneficial for reproductive health treatments for patients struggling with infertility. 

For example, AI-powered fertility trackers can inform users about their chances of conceiving based on their lifestyle and other factors. Besides, they offer the most suitable types of treatment. That translates into an innovative, personalized approach to each patient.

Similarly, ML models increase the chances of successful pregnancies in patients going through IVF journeys. By analyzing loads of patient health data and images, algorithm-based software can score and select the healthiest embryos and the most quality sperm. All these increase the success chances of IVG by 15%, helping patients to start a family naturally.

How AI-driven embryo selection works
Figure 6. How AI-driven embryo selection works

Another vast area of AI services development is robotic-assisted surgeries and rehab. Developed to imitate the human mind, you can educate robotics-driven machines in collaboration with AI tools to perform as assistants during medical procedures and help patients through rehabilitation. 

This way, robots not only allow handling more patients without increasing human resources but also provide benefits like more precision during surgeries and quicker patient recovery.

6. Enhanced Data Collection & Management

As already mentioned, data collection using AI tools is easy and effective in the healthcare industry. EHRs, chatbots, and wearables help collect and exchange patient health data between healthcare facilities and specialists, providing immediate access to medical information. 

Besides, AI technologies like deep learning and neural networks allow organizing loads of the collected data extremely effectively, quickly, and automatically. AI recognizes different types of data, allowing labeling, filtering, and sorting it accordingly in the background with no additional human resources.

AI algorithms’ data collection and management capabilities are significantly beneficial to medical research. With so much valuable data, AI-driven data organizing is essential to draw meaningful insights. In addition, the automated labeling and filtering allow researchers to proceed to and focus on more complex tasks that require their intellectual contribution instead of being stalled by the monotonous ones.

How AI-powered data analytics works
Figure 7. How AI-powered data analytics works

AI algorithms also help ensure that your data is in order by preventing duplicates. When transferring or logging data, a duplicate record will be identified and removed, as well as you may be notified when some valuable information is missing in a record. This way, you get a clean set of data that is easily accessible and properly sorted.

One more area where AI tools benefit data management and use is personalized recommendations for wellness app users and smart device wearers. Based on the data collected on a particular user’s behavior, AI healthcare apps and devices learn the person’s preferences and suggest ways of improving their well-being, like taking a walk to reach a healthy activity level or easing female users’ PMS symptoms.

7. Better Data Security

Machine learning algorithms allow building tools that identify security risks and help prevent them from breaching medical and patient data, which is sensitive information. And with around 1,000 medical records breached daily, it is a considerable security contribution to the industry.

Among all, predictive algorithms can recognize potential malware based on existing cases and prevent it from affecting the software in a healthcare facility. You can also use behavioral patterns to determine a data breach or other suspicious events, so measures like automatically isolating sensitive information can be applied.

Besides, AI technology allows for solid patient data encryption to prevent it from being exposed or hacked. Much sensitive information is held in EHRs or other forms of data storage, and different users access it from various devices and locations. Therefore, it is crucial to monitor the data’s security and take quick measures, which AI allows doing.

8. AI-Driven Insurance Verification

An area where AI algorithms are changing the healthcare sector is insurance verification performed by artificial intelligence. Checking patients’ health insurance details and ensuring that there is no fraud requires time and attentiveness. That makes the process prone to human error.

Benefits of AI services development in healthcare
Figure 8. Benefits of AI applications in the insurance industry

Tools for insurance verification powered by artificial intelligence in healthcare release the burden of completing this task from medical staff while increasing the accuracy and security of the verification results. 

An integrated solution recognizes health insurance data, verifies whether it is authentic, and confirms that the chosen insurance plan corresponds with the patient’s request. In such a way, the insurance verification process for patients is not only automated but also faster and more reliable.

9. End-of-Life Care

Robotics and intelligent wearables can be excellent assistants for the elderly, capable of monitoring their health and providing them company. And because they are connected to AI-driven software, the tools will react immediately in case of any life-threatening event. That eliminates the need for retirement homes while providing attentive patient care.


AI healthcare apps are transforming the industry with the opportunities they provide. Early disease detection, improved treatment, better management, and security of healthcare data are just some new capabilities artificial intelligence has brought to the healthcare sector. If you are thinking of making the most use of the potential AI can add to your application, contact us to develop a custom AI-aided solution.

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