Researchers and scientists consider artificial intelligence (AI) as similar to electricity; it will be a transformative tool in every industry, even in healthcare.
What will AI bring in the future?
Predictions for 2019 claim there will be an increase of AI transactions in healthcare. To support this, more than a third of hospitals and healthcare institutions plan to integrate AI into their system within the next two years.
However, AI still faces a lot of challenges in the field of healthcare, especially when it comes to data protection and predictive solution, which are discussed below.
Viable Dataset from the Healthcare Field
Data are the primary source of learning of machines, including AI. Moreover, data from the healthcare field are not an issue considering that the majority of the institutions can provide various and vast medical data.
However, the issue here is data handling, which means the combination, filtration, and identification of viable data to feed the system. It’s critical to note that AI data must be curated and adequate in order for the system to be successful.
Data sets must be robust in order to ensure that the learning system applies and understands what it is constructing. To ensure high-quality data, human touch still plays an essential role in the process. These curators must ensure that the data are accurate, uniform, and complete for ease of system adaptiveness.
In relation to having robust data, it is also important to note that another challenge of AI in healthcare is the manner of constructing medical solutions.
The use of AI by medical institutions goes to show that it is expected to provide accurate and expert medical results and analysis. Nonetheless, some medical practitioners have noted that AI use in hospitals is often disappointing because it can disrupt that relationship of the patient and the physician.
Therefore, it is critical to ensure that AI use in healthcare does not become a burden for both the patient and the physician. Healthcare providers must understand that AI cannot be used as a substitute for seeking help from a physician.
The primary goal of the application of AI in the healthcare system is to ease the burden of patients and physicians. It aims to save time and other resources and provide a more accurate diagnostic result.
In relation to the issues above, interoperability is also cited as a challenge of AI in healthcare. First, interoperability is the ability of the machine to synthesize data and communicate with one another and use information from different systems.
However, this type of systems can be expensive, especially if the user expects to get real-time information or answers. Moreover, it will also require different system structures in order to manage the different functions expected from the AI.
To resolve this, researchers and physicians can work on an AI system that can help physicians in identifying those who may not necessarily need medical attention in the hospital. Alternative solutions can then be provided to these individuals based on the data analyzed the by the system.
Data security and the breach isn’t only an issue in AI but almost in all system that collects data. Data collection also raises privacy issues, especially in the case of data set about the health history of an individual.
Some of the concerns raised in this issue include the following:
- Ambiguous data collection
- Lack of knowledge on how data are used or how the machine learns with the data provided
- Accountability on the automated decisions made by the system.
Solutions are being developed in some of the data security issues highlighted and more. The proliferation of AIs in different fields has paved the way to creating solutions and even enhancing data security in order for the users to be confident in sharing and storing their data.
With all these issues cited, it can be deduced that human touch will always be an essential part of technology in order to bring balance. Physicians will always be part of the ever-evolving aspect of AI and healthcare, especially when these two are intertwined.
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