As time progresses, new technologies and innovations developed to make our lives a bit easier. It all boils down to growth and efficiency! Similarly, healthcare has been investing in this newfound and developing area called machine learning. So, how does machine learning in healthcare change the dynamics of treating patients? And what are its benefits? Keep reading our article to know more.
Machine learning can prove to be a useful asset in the healthcare industry as it sure does have benefits more than one.
What Is Machine Learning
Machine learning might seem like a term that is new to everyone. But, in fact, it is used in nearly every operation that we come in contact with. It’s there, but we just didn’t know it had a technical term!
The speech recognition feature that you use for searching data on your smartphone is powered by this smart AI (artificial intelligence). Open your Google Photos and you’ll get an automatic tagging selection on your group pictures (image recognition). We’re pretty sure you must’ve used GPS apps for tracking traffic in real-time or finding the best possible route. Self-driving cars are also coming slowly to the automobile market. All of this comes under machine learning.
To put it in definition, machine learning is a type of AI that is programmed to give the best possible solutions by recognizing patterns on sets of data. When data is fed into the machine, the AI learns from it, and thoroughly analyzes each detail. The more data fed, the clearer and better are the outcomes it determines. There isn’t much human involvement as tasks are performed anonymously.
Due to how potential this program is since it has a wide range of applications, it’s a point of interest that’ll never fade away. It’ll just keep building and upgrading, and will in turn reduce human workload. And, no doubt, the healthcare industry has a fair share of machine learning in its systems as well.
Benefits Of Machine Learning In Healthcare
There are many benefits of implementing machine learning in healthcare. With AI taking care of tasks that would require a separate workforce altogether, medical practitioners can now dedicate more time and resources to the treatment of their patients. Here’s a list of those tasks that machine learning works on to benefit healthcare:
- Classification – With special machine learning algorithms, computers can find out the type of disease you’re dealing with. Although this can be done by a healthcare professional, a machine learning program will determine the results faster so that treatment can begin at the earliest.
- Recommendations – You don’t need to actively search for patient records. Machine learning algorithms will provide all the necessary patient information, allowing medical practitioners to have everything at one glance.
- Clustering – A machine learning program will group and analyze similar cases together. With the data input, the machine will span a wide range of practical solutions for effective treatment.
- Prediction – This type of AI can predict the illness based on the patient’s medical data. Although such predictive machine learning algorithms do not eliminate medical uncertainty ( not knowing how to go about with the diagnosis), it helps in giving doctors a rough understanding of what the possible ailment could be.
- Anomaly Detection – With the input statistical data, a machine learning program will study peculiar patterns and will help to detect if anything is abnormal. This is useful to determine any other odd symptoms so that the doctor can administer treatment immediately.
- Automation – Repetitive tasks such as data entry, scheduling appointments, inventory management, etc can take a lot of time and resources. Why not leave these mundane tasks to AI?
- Ranking – Machine learning helps in ranking relevant information first. This helps to make searching for records much easier and convenient.
How To Use Machine Learning In Healthcare
Clinical Decision Support Systems
Clinical decision support system tools path the way to efficiency and accuracy in healthcare. Scanning through each patient record to determine the possible problem and treatment by a doctor is a strenuous task. Clinical decision support systems cut that work for you. With the large amount of data they have, clinical decision support system tools scan through each record in no time, detect the possible ailment, prescribe diagnosis, and improve overall patient care.
Here, doctors can work more efficiently and quickly and its use nullifies the chances of administering the wrong medication.
Smart And Efficient Record Keeping
Data entry is a monotonous task. And regularly updating the system and keeping track of patient information is quite the challenge. That’s why many healthcare institutions have adopted OCR (optical character recognition) that scans the doctor’s handwriting and stores the data in the system. Other machine learning tools then analyze this data and then use it to improve patient care.
Machine Learning In Medical Imaging
All this while, healthcare institutions have been using traditional means of medical imaging (for eg: x-rays). But, it has some limitations in terms of anomaly identification, case grouping, and overall disease research. By going digital and giving machine learning a chance, we can also get deeper data analysis of the patient, which can be used to treat the patient better.
Medical Billing
The medical billing and coding industry is a billion-dollar industry. The amount of outsourcing of bills done by hospitals to specialized organizations is done much more than you’d ever imagined. Even these companies that help hospitals in organizing their bills use some form of AI applications. It helps in keeping things systematic and error-free.
A Few Of India’s Top AI Organizations
- Sigtuple: If you’re thinking about research, Sigtuple is one of India’s top AI organizations that uses machine learning to provide solutions for medical diagnosis and screening purposes.
- Predible Health: An organization founded in 2016 that specializes in using AI for diagnosing liver and lung cancers.
- Niramai Health Analytix Private Limited: This organization developed software that detects breast cancer at an earlier stage. It’s easy to use, and economically inexpensive as well.
By making the right use of machine learning in healthcare, you can definitely organize your practice and make it more efficient.
Conclusion
Although many have implemented AI in their medical institutions, it’s high time that more hospitals in India invest and recognize the importance of machine learning in healthcare as it enhances patient experience and patient care. We have also used a fair share of AI in our ImmunifyMe app. By using AI, we’ve developed a program that enables you to track the growth of children. It also helps to detect any anomalies at an early stage so that parents can consult their doctor at the earliest. Check out the app to make your practice not only more efficient but also effective.
FAQs On Machine Learning In Healthcare
How Is Machine Learning Used In Healthcare?
Machine learning has a wide range of applications in the healthcare industry. But these are 4 main ones that have sparked innovation in the health sector:
- Clinical Decision Support Systems
- Smart And Efficient Record Keeping
- Machine Learning In Medical Imaging
- Medical Billing
What Is Machine Learning?
Machine learning is a type of AI that is programmed to give the best possible solutions by recognizing patterns on sets of input data.
What Is Machine Learning In Diagnosis?
Machine learning is the future of patient diagnosis. It allows doctors to administer the right treatment effectively and quickly. And the best part of implementing this branch of AI in the healthcare industry is that it’s accurate and improves patient care.