How mobile apps and Machine Learning technology have revolutionised modern healthcare?

 

Mobile apps brought some of the revolutionary changes for the entire healthcare industry. Whether in respect to the way patients are now relating to the doctors or how they can access their electronic medical records, mobile apps have penetrated every nook and corner of the healthcare sector. 

But mobile apps also opened up the lock gate of other tech innovations for the sector. For example, artificial intelligence and Machine Learning technologies have recently made revolutionary value additions to the healthcare industry. These technologies have penetrated the industry deeper, from lowering the cost of healthcare to enhancing the healthcare delivery system to helping innovations in treatment procedures to facilitating personalised healthcare. 

Here we will explain these revolutionary benefits of mobile apps and machine learning in the healthcare industry. 

 

Apps Allowing Instant Healthcare Access 

 

When you need to wait in a queue to fix a doctor's appointment to visit his facility on a deferred date and time, those times are gone. Such inconveniences have become a thing of the past simply thanks to the on-demand doctor appointment apps or medical consultation apps. As a result, the app developers India are now sought after by the country's healthcare facilities for developing remote patient care apps. 

 

Whether it is a case of emergency or a chronic health issue, you can visit a doctor personally right through your mobile screen and get immediate consultation and medical advice. 

 

Patient Monitoring Became Simple 

 

The connected medical gadgets and an IoT app can now help caregivers and doctors keep watching patients' movements, vital statistics, and signs. Such apps are particularly useful for patients who need to be closely monitored from time to time or patients suffering from psychological trauma or behavioural problems whose movements need to be monitored. 

 

Quick Access to the Medical Guide and Drug Details 

 

Today's physicians often browse their handheld screens when writing prescriptions or consulting manuals for certain critical cases. This instant access to medical knowledge and resources helped improve the medical treatment precision and quality while helping them to deal with more patients in a limited period of time. 

 

Now, let us have a quick look at some of the ways machine learning technology made a significant impact on the healthcare ecosystem. 

 

Detecting Patterns Through Imaging Analytics

 

These days, modern healthcare facilities rely on imaging analytics powered by machine learning algorithms to detect various recurring patterns and subtle changes. These patterns and changes detected by machine learning algorithms often help detect lethal diseases such as cancer. Recently Google's ML algorithm could successfully detect carcinogenic tumours in mammograms.

Personalised Treatment based on Precise Predictions 

As Electronic Health Records became common in the healthcare industry, this huge amount of data continued to be viewed as a rich reserve of data that can draw precise insights on a patient's crucial health signs and treatment responsiveness. In addition, machine learning algorithms and data analytics are drawing individual patient insights to ensure a personalised treatment that can yield far better results. 

The IBM Watson Oncology is a machine learning-based solution that utilises patients' medical data and medical history to draw the most precise health insights. Thus, it allows doctors to plan highly personalised treatment plans that can ensure better responsiveness and results. 

Modern Drug Discovery and Research  

Machine learning algorithms and tools also made great penetration in the field of drug research and discovery. From the stage of initial screening of the key compounds of a drug to the estimation of the responsiveness and success of the drug based on different biological factors, machine learning is continuing to help modern drug research and discovery. 

Understanding the huge potential of Machine Learning technology in drug research and detecting the effectiveness of various medical compounds, pharma manufacturing companies are now hell-bent on utilising the technology in their research and production facilities. Particularly, machine learning technology is helping pharma companies to do away with high-risk clinical testing while ensuring more precise outcomes well in advance. 

Advanced Diagnosis of Diseases 

Machine Learning has particularly made deep inroads into the diagnostic procedures and helped detect ailments easier than ever before. For example, certain diseases that are hard to detect in the early stages because of their confusing characteristics and symptoms can easily be detected by using machine learning algorithms. 

IBM Watson Genomics already made significant inroads in utilizing advanced computing power in detecting early signs of cancerous tumours. By integrating cognitive computing, IBM Watson further made genome-based tumour profiling and sequencing easier, resulting in faster diagnosis and faster starting of life-saving treatment. 

Robotic Surgery

There can be hardly any doubt that robotic surgery helped doctors save more lives in case of complicated surgeries where precision is the most critical element. When it comes to performing the most precise operations in small and tight areas within the human body, intelligent robots are more articulate and accurate than most accomplished surgeons in the field. These surgeon robots are run by powerful artificial intelligence and machine learning algorithms to learn and adapt to surgical challenges quickly. 

Individualised Health and Wellness

By understanding every person's medical history and individual data, ML-powered healthcare and wellness programs come with highly customised plans to prevent certain imminent health problems while suggesting diets, practices, and medicines that individuals should take to stay clear of health problems. This kind of machine learning based on predictive healthcare and wellness for individuals is set to become a future trend. 

Conclusion 

Both mobile apps and machine learning technology have penetrated the healthcare system beyond the scope of rebuttal. In the years to come, they are only going to be synonymous with advanced and modern healthcare systems.