AI and Data Annotation in Healthcare

In this era of advanced technology, the healthcare field is under enormous pressure to improve patients’ quality of care and experiences. This involves investing in intelligent solutions for better decision-making in times of emergencies. For such scenarios, Artificial Intelligence and data annotation help increase the overall quality of healthcare and lower costs.

AI and Data Annotation in Healthcare

What are AI and Data Annotation?

If defined in the simplest words possible, Artificial Intelligence is all about simulating human intelligence processes carried out by machines, especially computer systems. Although the simulation is nearly perfect, there is still a need for humans to collect raw data and feed them into AI so that the machines can perform human-like actions.

This is where AI data annotation comes into action because it is a process where a human annotator gets involved in the raw data set and adds labels, categories, and other contextual elements so the machines can easily read and perform accordingly. Some types of data annotation include:

Usage of AI in Healthcare

Here are some of the most prominent uses of AI in healthcare:

1- Lowering the costs of healthcare:

With Artificial Intelligence, patients can now quickly know what to do before surgeries, as proven by PrehabAI that is developed by Peerwell. This PrehabAI app takes all the necessary information from the patients and prepares a plan that the patients can follow daily to get them ready for the surgery. If apps like these don’t exist, the hospital staff will have to create all the plans, and such procedures can require patients to stay in the hospital for days, increasing their overall treatment costs.

2- Patient’s Intake Management:

With Covid-19 making all the usual things entirely different, the same is the case for direct interaction of doctors with patients. To reduce the exposure of the virus to doctors and patients, many hospitals are now using robots to notice all the necessary symptoms by taking the temperature of the patients and detecting if there is any chance of virus. This helps in saving loads of time for the doctors and the salary costs of the hospital management.

3- Medical Imaging:

Doctors reading medical images like X-rays, CT scans, MRI takes quite a long time of almost 30 minutes to determine whether there is something serious to worry about. This is not a problem anymore since AI performs the same duty as humans, which is a lot faster. The process may take around 15 seconds to determine if there is something life-threatening or potentially harmful for the patients.

Conclusion

The use of AI data annotation is now proving to be potentially significant to assist healthcare workers in many aspects when it comes to taking care of patients and making a different diagnosis. There is no denying that the diagnoses made by AI are the same or even better compared to humans; however, AI has not yet completely replaced humans in healthcare, and this may take a significant amount of years to happen.

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