In the United Kingdom researchers successfully deployed four AI algorithms that were found to be more effective than human doctors at predicting a heart attack. Find out what artificial intelligence technologies boost healthcare apps today.

Artificial intelligence is touching many aspects of contemporary life. One area in which it has a highly promising impact is within the healthcare industry. As an example, Google’s DeepMind is currently employing machine learning within the UK’s National Health Service to transform how it operates.

In recent times medical science is increasingly recognizing the power AI and augmented reality systems. The reason is the ability to process and find insights into datasets that are too complex for the human mind.

Mentalstack Team works with artificial intelligence, augmented and virtual realities in the healthcare field. In this post, we’ll tell how AI transforms the face of healthcare.

Healthcare Artificial Intelligence

Medical Decision Making

Humans are fallible and medical practitioners are human. The final result? Mistakes happen in the healthcare industry in the same way they happen in any other industry.

Radiologists, for example, examine around 200 cases a day and around 3000 images in total. This sheer volume of data can completely overwhelm radiologists.

This is where AI can come into play. AI has the propensity to reduce the volume of data that radiologists examine and ease their workload. It helps them to more accurately detect health risks and take the optimal actions to reduce their impact.

Many people believe that AI apps will ultimately reduce healthcare costs and improve patient outcomes.


One promising project is that of Medical Sieve, which is currently being implemented by IBM. This cognitive medical assistant has been designed to detect radiology images more reliably and at a faster rate than humans. It will help cardiologists and radiologists make better decisions based on a combination of clinical knowledge and multi-modal analytics.

Improved Visual Diagnosis

Experts predict AI to revolutionize the healthcare industry by reducing the amount of time needed to identify hard-to-diagnose conditions. The healthcare apps will recognize the Alzheimer’s, cancer, multiple sclerosis, and rare disorders immediately. Check how augmented reality (AR) improves the Healthcare Industry today.

At present, physical examinations are a fundamental part of the diagnosis processes. For example, certain patterns of marking on an individual’s skin can help doctors to detect conditions such as measles. Certain behaviors such as slow movements and tremors can lead to Parkinson’s diagnoses. However, contemporary technologies are now taking diagnosis processes one step further through the use of AI technologies such as eye tracking, pattern detection, and facial recognition to develop systems that facilitate how practitioners diagnose conditions.

AI healthcare apps have the ability to recognize patterns, learn from these patterns, and subsequently make decisions according to the insights they gain from them. For example, Google Photos incorporates a facial recognition software that allows users to search and catalog images of people amongst the thousands of images stored on the application.

When these AI systems interact with the healthcare setting, cataloged images can be used to screen patients against thousands of other similar cases to pinpoint the physical symptoms that are unique to a given medical condition.

Recognizing Facial Features

The same technology that AI systems currently use to detect faces in digital photographs has been successfully applied to identify the physical features of certain medical conditions.

For example, there are the Face2Gene phenotyping applications that employ machine learning and face recognition to help healthcare providers identify rare genetic medical issues. These applications have the ability to extract data points from a photo and compare them with images of patients diagnosed with a similar disorder.

Detecting Mental Health Issues

People who develop mental health issues often exhibit certain behaviors that make their condition clearly apparent. In the case of children and students, mental conditions need to be taken into consideration when developing appropriate eLearning solutions. Some medical practitioners are now turning to AI to more quickly and effectively detect mental health issues.

For example, the RightEye’s eye-tracking technology operates an AI-driven autism test. It allows medics using eye-tracking to identify the early stages of Autism Spectrum Disorder at the age of 12 months.

During the eye-tracking test, the tool screens children through presenting them with a series of images. Based on these images, health care providers are able to detect which child has a healthy brain; i.e., they are able to focus on faces on the screen, and which are exhibiting autistic visual tendencies; i.e., they focus more on objects other than faces on the screen.

Detecting Malignant Diseases

Some skin markings, such as rashes, can be an indication of an underlying medical condition. By identifying these skin issues, medical practitioners can more effectively detect malignant conditions such as skin cancer and more and more medical practitioners are using AI algorithms for this purpose.

DermaCompare is a prime example of a system that employs AI algorithms. It compares images of melanoma moles with 50 million known moles uploaded by doctors and patients throughout the world.


Innovation in artificial intelligence is powering a new generation of health monitoring applications that empower patients to keep abreast of their health and well being.


For instance, Vi is the artificial intelligence app that uses bio-monitoring earphones to measure your heartbeat and your fitness data to learn about how your body is responding to exercise and to tailor training workouts for you. It is, in effect, an AI personal trainer.

Medication Adherence

Degenerative cognitive disorders such as Alzheimer’s disease lead patients to exhibit symptoms such as impaired memory function, reasoning, and problem-solving skills. This can prove a challenge for healthcare providers when a patient forgets to take medication or are no longer physically able to keep up with a treatment plan. Artifical intelligence has the potential to provide a solution for the healthcare industry.

For example, AICure app uses a combination of a smartphone camera, artificial intelligence, and facial recognition software to confirm a patient has taken their prescribed treatments on schedule.  The AI and the facial recognition which confirms ingestion of the medication adapts to patient behavior over time.

Treatment Plans

According to Al Babbington, CEO of PrescriveWellness, sci-fi will become a reality in the next 20-30 years, by which point artificial intelligence,  the internet of things, big data and precision medicine will combine to provide Star-Trek like treatment, such as a full body bio-scan, complete with genetic mapping. Treatment will be fully personalized to the individual, along with complementary therapy and diet, making treatments such as chemotherapy seem as ancient and distant as leeching.

A further issue for healthcare professionals is that a treatment plan is often not a straightforward exercise. For example, medication may cause unexpected side effects, or the patient may prove resistant to the treatment. Furthermore, the patient may present new symptoms, prompting a revision to the original treatment plan or diagnosis.

Artificial intelligence can now solve the problem.

Traditionally, a doctor would consider treatments based on the patient’s specific medical condition, while also bearing in mind the individual’s medical history. Artifical intelligence, with its inherent data mining and deductive capability, can assist to make better informed and ultimately more accurate decisions.

IBM Watson for Oncology is a current example of a system that can scrutinize data in structured and unstructured clinic reports to draw powerful conclusions.  The data is used to assist physicians to identify key information from patient records and tailor a specific treatment plan to the needs of the patient.

Prompt Detection of Medical Conditions

A common problem in devising a treatment plan for rare medical conditions is that there is not a lot of previous cases and there is, therefore, a lack of medical plans for comparison.


In order to expedite diagnosis and treatment, medical practitioners are turning to ‘deep learning,’ a process that compares salient information with other extensive records. Enlitic is one such AI platform, for example, that interprets radiology images in an instance by comparing the image to other unique medical cases. The platform has proven to be 50% more effective at identifying malignant tumors than a human radiologist according to a recent article in the Economist.

An algorithm has also been developed for Emory University with the help of their Medical Research & Doctors, for a cloud-based research healthcare application that mimics early-stage AI bots. This suggestion based system, analyses a given patients symptoms and suggests a treatment based on the diagnosis.

Want to build a Healthcare App?

As you may see, artificial intelligence applications bring not only a breakthrough to the healthcare system improvement but the great source of revenue to the medical businesses.

For a custom development of the web and mobile healthcare or medicine applications considering artificial intelligence, contact us. We will provide you with a detailed estimation of timing and price for your project. Give us a call and we will give you a solid plan how we will turn your idea into reality.

Artificial intelligence has now started to show remarkable results and the potential to revolutionize healthcare for years to come. Medical systems which already make use of AI applications know how much profit the apps bring. Take a look at How Apps Earn Money to understand how it works. What was once the impossible dreams of science fiction is about to become a reality for patients and doctors alike.

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