How Healthcare Can Benefit From Machine Learning

It is estimated that by 2025, close to 100% of organizations will have implemented some form of Artificial Intelligence. And Machine Learning, which is a major subset of AI is likely to experience widespread adoption too.

And healthcare is one of the top industries that stand to benefit from the adoption of machine learning.

Why?

Integration of ML in healthcare will bring about cost reduction, efficiency enhancements, and overall better results.

For example, 70% of drug discovery costs can be cut down with the use of AI and ML.

But that's not all. Every healthcare organization can benefit from the application of machine learning. And today, we will be discussing the top 5 applications of ML that can benefit the healthcare niche. 

1. Accurate & Timely Diagnosis

Machine learning can be used to quickly analyze a lot of data. And by analyzing data from x-rays, ultrasounds, medical history, and symptoms, ML can offer a timely and accurate diagnosis. 

A lot of ML-based diagnostic solutions emerged during the pandemic and they did have a high level of accuracy. 

There's also an ML-based cancer detection app that can help predict the chances of skin cancer in patients.

2. Robotic Surgery

Most patients today prefer minimally invasive procedures. And ML-powered robots can help facilitate that even for complex cases.

The da Vinci robot, for example, can help reduce the time taken for the surgery, the recovery time, and the overall hospital stay, while being minimally invasive. Surgical robots use precision tools to perform surgeries and take feedback from previous surgeries, and data from EMRs in real-time. This minimizes human errors and the need for a lot of specialists.

3. Personalized Medicine

Not all medicines work in the same way for everyone. Yet, doctors are left with no option but to prescribe the same set of medicines to most people with the same ailments. By applying ML in healthcare, patient health records, environment and lifestyle data, and generic data can be collected, processed, and analyzed to offer personalized medicines and treatment places.

4. Dosage Accuracy

A step ahead of personalized medicine, dosage accuracy involves changing the medication dose in real-time situations. This type of hyper-personalized healthcare can be offered to patients by using ML models to monitor and asses patients' response to medicines and then improve outcomes by altering dosage accordingly.

5. Virtual Assistance

The lack of experienced healthcare professionals and primary caregivers is another key hurdle in the healthcare domain. ML-powered virtual assistants can help solve that issue.

By monitoring a patient's vitals, healthcare VAs can analyze symptoms and offer predictive treatment. This will reduce the number of hospital visits and ensure specialists don't have to spend time on unnecessary tasks.

There are many other ways ML can be used in the healthcare domain to yield stunning results. All you need to do is get in touch with Machine Learning experts and discuss your business needs.