Doctor’s: 3 Ways how AI and Machine Learning is going to Change your future!

When I was kid, the way doctor used to treat their patients, always amazed me. The 3 devices that they had to diagnose my disease were:

1.    Stethoscope

2.    An Analog Thermometer

3.    A Blood pressure monitor

If the they disease where little too complicated that could not be diagnosed with the aforementioned simple devices, I was sent to a pathological laboratory for basic blood test, urine test, or stool test, highest was an X-ray machine!

Labs were not complex either, they had few petri dishes, an analog centrifuge, test tubes, and a big X-Ray machine!

However, in 80% cases, it was doctor’s call and experience that detects the diseases and you may never have visited one of the labs.

Things changed a lot a lot over last 15-20 years, now, it’s no more a doctor’s call neither simple machines. Doctor’s went ahead and switched to data driven decision. Now they give you a list to tests from A-Z, and based on the results, take diagnose the issue.

1.    A digital X-Ray

2.    MRI

3.    CT Scan

4.    ELISA test and many more.

The moment they moved onto data driven decision, they clear the path for automation to help. If the decision is digital, who can interpret data consistently better than a machine? The second machine age started early, primarily in the area of radiology, blood chemistry, pathology. So, the new three areas evolved or evolving rapidly are.

1.    Data Driven Digital Lab tests

2.    Quickly classifying a disease

3.    Using automation for surgery

First time, when I visited a hospital, a couple of years back for some of my family member, doctor asked me, do you need a robotic surgery or manual? I was stunned! I knew robots are going to be better over human as they can cut accurately over a human, and their decision will be data driven but I was worried too, what if the software have some bugs, what if the power goes off, etc. However, end of the day I decided to go with robotic surgery.

Now even some big hospitals are like Manipal hospital (a big chain in India), using IBM Watson to diagnose cancer; classifying the malignant vs. benign tumor. So, does this mean the job a doctor is no longer safe in second machine age? Yeah, right you are! Some par of the jobs for doctors will no longer exist.

1.    Radiology – Computer can accurately read the X-Ray, MRI, CT scan report, same with you ultra sound.

2.    Disease detection – With all data now electronically available to the computers, the machine learning model can detect disease more accurately and consistently. So, the same results, will not have different opinions, one by doctor sitting in remote African country vs. John Hopkins!

3.    Accurate surgery- Surgery can be done microscopically, accurate. This is instead of completely nephrectomy, you can now have partial nephrectomy and save half the kidney!

So, the next question, I get from ‘’to be doctors” or medical enthusiasts, does this make sense to study, my answer is always, yes, you should! The jobs will not change as, we do not need domain experts, in actual, the experts, requirements would increase. 

Remember, the knowledge of domain expertise is more when you are building bots with supervised learning models.

Secondly, the doctor’s job is not just diagnosing the problem but also to interact with the patient and their family and friends, until the end of a journey. This includes emotions, empathy, providing confidence, calm people down, explain the problem. Agree or disagree, we are not at a stage, where these can be done by the bots, or even if it’s done by the bots, it will be accepted by the humans.

So, in a nutshell, doctors should build on their technical skills and human skills much more than before but the key of ‘domain expertise will remain there’.

Abhijit Ghosh is an enthusiastic learner with deep understanding of both data, technology, and concurrent people management policies and practices. An exceptional achiever, well-rounded, multilingual, culturally aware professional with a strong background in building and leading multi-discipline, geographically dispersed teams to manage complex operations and automation. Specializes in highly cross functional collaborations with Operations, Finance, HR, Data Management in financial services industry. He has over 17 years of hands-on management experience in planning, creating, data products and solutions through design thinking. Extremely skilled strategist for robotics and cognitive automation solutions

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