Every industry is walking through the data science transformation. While IT, BFSI, and marketing are under the spotlight of data science career transition, healthcare data scientists are silently taking toward its most advanced era. Due to the global pandemic of COVID 19, medical science has exposed ample scopes in AI and Deep learning during the last year.

Yes, amongst all the industries, healthcare owns the most promising opportunities for advancement through data science. Let’s look at how data science and artificial intelligence transform our healthcare sector into supernatural power. 

What are the applications of data science in healthcare?

  1. Automated Diagnosis by Medical Imaging

This has been the very first step of the healthcare domain to enter into the world of data science. In conventional processes, doctors analyze medical images like CT-Scan, X-ray, MRI, etc., with manual effort. 

Not always, but sometimes manual effort might lead to the wrong diagnosis. It’s possible that with the human eye, some nano-level of abnormality got overlooked. Making the changes of such misdiagnosis almost zero, data science has revealed the auto-analysis process of each image segment, under which nano deformities get identified.  Deep learning. The most advanced branch of data science has made magic. Advanced machine learning algorithms that resemble the human neural network is the key to this medical advancement. The specific technique used for image recognition and analysis is Support Vector Mechanics.

  1. Operation management of healthcare centres

Operation management is the most cost-sensitive department of any industry. But in the healthcare domain, the matter becomes more crucial as management has to take care of both the employees and patients in terms of 24×7 service efficacy without making the workforce stressed. 

Besides, monitoring and identifying the level of challenges that every patient may face during their treatment period or during discharge is also a matter of concern. 

Several data analytics software has now made this process simple. Now, even from lakhs of patients, with the help of AI-powered predictive analysis software, a health care operation management unit can identify the patients with a greater degree of risk during discharge or even the post-discharge phase. 

This is all about patient management. But what’s about people management. Yes, tracking, validating, modifying, personalized training and development for each employee is a headache. Not only that additional workforce has to be appointed for such people management tasks.  Automated AI-enabled clinical software and application now easily track healthcare employees productivity, treatment accuracy, patient satisfaction rating for doctors and other staff in a flawless manner, and most importantly, with a minimal amount of human effort.

But,  this is not the end of data science magic. In earlier days, so many small to medium healthcare organizations were bankrupt due to wrong financial investments or improper health insurance history of patients. 

With the help of several business intelligence software, healthcare can easily identify the associated financial risk, financial crisis, or any other further problem in advance. Take steps like an advance discussion with insurance companies, negotiation of payment methods, accordingly.  

AI and Deep Learning
AI & Deep Learning in HealthCare
  1. Discovery of drugs by Artificial Intelligence

Can you imagine how much a drug discovery cost?

Sometimes this cost can even cross billions. However, this is average data only. In actuality, the cost of drug discovery can be beyond our imagination. But this is not the real concern. Instead, the concern is time.  Discovery of a drug and launching of the same can even take more than 15 years. Yes, it’s true. Just remember, almost two years will be, COVID is roaring across the world, but no medicine has yet been revealed. 

But yes, vaccination has already started, and no surprise that such quicker launching of vaccination has only been possible due to the power of AI. ML, and deep learning

Each drug discovery involves a series of data analytics regarding the mutation profile of a virus, fungus or anything else. Apart from that, before launching the drug in the market, pharmaceutical companies have to analyse the patients’ data of non-human and human trials. At this point, the major concert that makes a drug discovery time consuming is the sensible and proficient analysis of patient meta-deta, historical data.

So, who became the saviour here? Big data technology- the most promising division of data analytics. Generation of insight from tons of data is just a matter of a few hours for Big data applications. 

With the help of complex machine learning and deep learning algorithms, researchers can easily predict the probable pattern of the medicine action within human bodies. 

  1. Health Monitoring and remote assistance

As you think about health monitoring, what comes first to your mind while reading this data science-related blog? The lage devices in ICU units? Well, you have thought in the right direction, but you are thinking too much.

Do you wear a fitness band? At present, this the handiest example of an AI-enabled health monitoring gadget. 

In health care centres and even in-home care, doctors and healthcare workers use portable health monitoring devices that remain connected with remote control rooms or specified mobile devices. Again it’s the magic of data science.

So, monitoring real-time health data for thousands of patients at the same time is no more an impossible task now. 

Now come to the remote/virtual assistance process. Nowadays, plenty of health apps and sites can give you a diet chart or daily routine to follow based on your input related to health conditions and information. The best example here is getting daily tasks recommendation for depression or Alzheimer’s diseases.

No need to say who is the boss here. Yes, it’s again the automated application developed with the help of ML algorithms.  

  1. Diseases prevention

Lots of life threading diseases do not show early symptoms. So, when the symptoms finally appear, it becomes too late to save the life. 

AI has played a vital role in the prevention of such diseases. Although not much, some life-reading diseases can be tracked at early stages with several AI-enabled health applications. 

Zika virus detection via metabolic markers is now possible.

Lots of other diseases are in the experimentation stage and showing remarkable degrees of research advancement.   

How Data Science has helped the healthcare domain to fight against COVID?| 

Here lies the biggest key reason why data scientists demand in AI is experiencing a steep hike in the healthcare domain within the last 1.5 years.  

COVID-19 virus has infected billions of patients worldwide. So many times, this virus has undergone mutation, different types of strains are now available. So do you think tracking and real-time data for this virus behaviour in the human body and against several medicines can be tracked with the human brain!

AI and deep learning have played a vital role in predictive analysis for coronavirus behaviour. That’s why we have at least the vacation in the market. It’s true, the second wave has already restarted smashing up human life, but still, we can’t deny that at one point, we succeeded to handle the first wave. It’s only because of AI-powered predictive analysis. All the research centres, healthcare centres, and governments got timely updates about the number of patients affected, the number of fatal cases, deaths, and recovery.

The patterns of symptoms, even tracking and identification of repeatedly changing symptoms, have remained possible only because of efficient AI and deep learning. If you are interested to know more about AI and ML applications in COVID-19 prevention, treatment, and diagnosis, visit AI and data science tools up to battle COVID-19.

If you belong to the healthcare sector, then its high time for you to plan a data science career transition. 

But confused, where to start? Visit www.skillslash.com/

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