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SUNDAY, MAY 18, 2025
Navigating the opportunities and obstacles of AI in the healthcare industry

Thoughts

Ahmmed Madhurja
11 February, 2023, 08:10 pm
Last modified: 11 February, 2023, 08:16 pm

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Navigating the opportunities and obstacles of AI in the healthcare industry

Ensuring data privacy and security, addressing bias in algorithms and the shortage of skilled personnel with the necessary expertise in AI are just a few of the challenges that must be overcome for a successful implementation of AI in healthcare

Ahmmed Madhurja
11 February, 2023, 08:10 pm
Last modified: 11 February, 2023, 08:16 pm
AI-based virtual assistants are increasingly being used in healthcare to provide patients with access to information and support. Photo: Reuters
AI-based virtual assistants are increasingly being used in healthcare to provide patients with access to information and support. Photo: Reuters
AI-based virtual assistants are increasingly being used in healthcare to provide patients with access to information and support. Photo: Reuters
AI-based virtual assistants are increasingly being used in healthcare to provide patients with access to information and support. Photo: Reuters

In recent years, the use of Artificial Intelligence (AI) in healthcare as a way to improve patient outcomes and streamline healthcare processes has gained significant attention. AI has the potential to revolutionise the healthcare industry by improving patient outcomes, reducing costs, and increasing efficiency. According to a report by World Economic Forum in 2018, AI in healthcare can potentially save an estimated 20-30% of healthcare spending in the developed world.

One example of AI being used in healthcare is in the field of radiology. AI algorithms can assist radiologists in detecting and diagnosing diseases such as cancer by analysing medical images and identifying patterns that may be difficult for a human to detect. A study by researchers at Stanford University found that an AI algorithm was able to identify lung cancer on CT scans with a similar level of accuracy as experienced radiologists.

Another example of AI in healthcare is in the field of drug discovery. Algorithms can assist in the process of identifying new drug candidates by analysing large amounts of data and identifying potential drug targets. This can save a significant amount of time and resources compared to traditional drug discovery methods. A study by researchers at the University of Cambridge found that an AI algorithm was able to identify a new drug candidate for a rare genetic disease in a fraction of the time it would have taken using traditional methods.

In addition, AI-based virtual assistants are increasingly being used in healthcare to provide patients with access to information and support. These virtual assistants can answer patient questions, provide medication reminders, and even assist in scheduling appointments. One example of this is the virtual assistant "Amy" developed by the biotech company X.AI, which can assist patients in scheduling appointments with healthcare providers.

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Despite these potential benefits, there are also challenges to implementing AI in healthcare. One major concern is data privacy and security, as large amounts of sensitive patient information have to be collected and stored by AI systems. 

Additionally, there is currently a lack of regulation and guidelines for the development and use of AI in healthcare, leading to uncertainty about how to ensure patient safety and privacy. There is also a shortage of skilled personnel with the necessary expertise in AI to develop and implement these systems.

There is also the potential for bias in the algorithms. If the data used to train the AI systems is not representative of the population it will be used on, the AI systems may make inaccurate or unfair decisions. This can be particularly problematic in healthcare, where any decision can have serious consequences for patients. 

For example, if an AI system used to predict patient outcomes is trained on data from a population that is not representative of the population it will be used on, it may not accurately predict outcomes for certain groups of patients.

The cost of developing, implementing and maintaining AI systems can be high, and it may be difficult for healthcare organisations to justify the cost when there is a lack of evidence of the long-term benefits of AI. Moreover, the cost of retraining healthcare professionals to work with AI systems may also be significant. This can be a major barrier to adaptation, particularly for healthcare organisations with limited budgets.

In conclusion, while AI has the potential to revolutionise healthcare, there are also significant challenges to implementing it in healthcare. Ensuring data privacy and security, addressing bias in algorithms, and addressing the shortage of skilled personnel with the necessary expertise in AI are just a few of the challenges that must be overcome for a successful implementation.

Ahmmed Madhurja is currently a 4th Year student, majoring in marketing at the Faculty of Business Studies (FBS) at Jahangirnagar University.

Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the opinions and views of The Business Standard. 

Artificial Intelligence / health

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