Artificial intelligence, the ability of computer systems or digitally controlled robots to perform human-like activities is the biggest
Artificial intelligence in healthcare has the potential to transform different sectors such as administration, patient care, and pharmaceuticals.
Artificial intelligence in healthcare comes with the challenges of bias and fairness in patient care across different regions all over the world. This is the reason why
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Artificial intelligence in healthcare provides several benefits for patients, healthcare providers and the healthcare sector for different economies. One way in which artificial intelligence makes healthcare better is the ease of
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According to Harvard's School of Public Health, using artificial intelligence to make diagnoses may reduce health costs by up to 50% and improve healthcare by up to 40%. At the
Genetic medicine can save a lot of lives:
The data collected by these sensors can be analyzed by machine learning algorithms to provide insights into an individual’s health status, enabling early detection of health challenges and the provision of personalized healthcare. The benefits of artificial intelligence are uncountable and bound to address the healthcare disparities that affect patients worldwide. The regular traditional approaches that aim to make healthcare accessible to all, have not shown results.
Artificial intelligence helps analyze large datasets for patterns, correlations and predictive patterns that are difficult to identify through traditional analyses. Artificial intelligence can help identify hidden mechanisms and causes of healthcare disparities. AI has many advantages compared with traditional strategies for addressing health disparities, notably in its ability to uncover unexpected correlations and relationships that have remained unidentified in human-driven analyses, offering new insights. Populations that have been historically marginalized and experienced barriers to healthcare will now be fully represented, with full access to healthcare. To fully address these health disparities, it is important to ensure equity in all stages of artificial intelligence use and processes in healthcare. The best way to implement that is to provide more diversity within the teams developing and deploying artificial intelligence algorithms. Greater representation from various stakeholders from diverse backgrounds, including policymakers, researchers, clinicians, and ethicists, must be included to ensure different voices and perspectives are included in the research team. This is because diverse research teams are more able to identify potential disparities, inequities, or underrepresentation that could lead to bias.
Despite the benefits that artificial intelligence offers to the field of healthcare, there are some challenges. A significant challenge is that of bias:
Bias affects predictive artificial intelligence tools: a
Another example is an AI algorithm used for predicting future risk of breast cancer which suffers from a performance gap where black patients are more likely to be assigned as “low risk” incorrectly. In addition, an algorithm trained on hospital data in Ghana might not perform well in the United States, as the patient population, treatment plans and medications may differ. A pressing challenge that artificial intelligence brings to healthcare is data safety. Concerns are being raised on data safety because private entities control most artificial intelligence technologies. This means that healthcare providers, hospitals and public bodies have more control of patient healthcare data. There is also the risk of data breaches through artificial intelligence methods. The ability to anonymize patient health data may be compromised or even nullified in light of new algorithms that have successfully reidentified such data. This could increase the risk to patient data under private custodianship.
Liability is another problem for the use of artificial intelligence in healthcare. “If a doctor misdiagnoses a patient or gives a wrong treatment, the doctor can be sued. If artificial intelligence algorithms make costly mistakes that result in complications for a patient, who is to be sued?” The problem is that artificial intelligence is not a human being and cannot be directly responsible for acts of negligence. There is a significant obstacle preventing the widespread adoption of artificial intelligence in healthcare: __i__mplementation. There is a knowledge gap in the utilisation of artificial intelligence tools in healthcare as many healthcare workers do not fully understand the concept of artificial intelligence. In addition, novel technologies such as artificial intelligence are sometimes resisted by healthcare leaders, delaying their implementation. This is because these healthcare leaders do not see how artificial intelligence fits into existing healthcare work practices and processes.
A study conducted among doctors revealed resistance to the use of artificial intelligence in healthcare. Some healthcare providers view artificial intelligence as expensive so implementation becomes a challenge because of the perceived cost. There is also the additional cost of training healthcare workers on the use of artificial intelligence tools. Another reason why artificial intelligence costs so much is the infrastructure, equipment, and technical requirements required to set up its tools in a healthcare system. Healthcare leaders may not want to adopt artificial intelligence in healthcare because of the fear of technology dependency. Some healthcare workers and leaders believe that regular use of artificial intelligence tools will make healthcare workers unable to improve their clinical skills and lose their communication skills that improve patient relationships. They also fear that with artificial intelligence taking over healthcare, their jobs will be taken over. The fear is that artificial intelligence tools will replace healthcare staff. All these challenges make artificial intelligence in healthcare inaccessible in some regions of the world, especially in low and middle-income countries where finance is a major determining factor in accessing quality healthcare.
For every problem, there is a solution. If we want to utilize artificial intelligence for our own benefit in our hospitals, we must ensure equitable access to artificial intelligence in healthcare. One way to ensure that is by providing funding and support: a good example is when the White House announced a $140 million investment for the National Science Foundation to assess generative artificial intelligence (GenAI) systems. The Food and Drug Administration (FDA) has also taken steps by releasing a beta version of its regulatory framework for medical device AI used in healthcare. If funding is provided, the cost of artificial intelligence systems will be reduced and these tools will be more accessible to healthcare staff all over the globe.
Regulatory policies are the solution for the data concerns and legal issues associated with artificial intelligence in healthcare. Policies can help to address the challenges of bias, promote diversity, increase transparency, and enforce accountability in artificial intelligence systems. Regulatory policies can help utilize the potential of artificial intelligence to improve healthcare delivery and reduce costs while ensuring fairness and inclusion. These policies should mandate the regular auditing of artificial intelligence systems in healthcare to eliminate bias and functionality errors. Policies should also include guidelines on the use of artificial intelligence in healthcare and allocate funding for the healthcare benefits of the marginalized. There are several examples of how artificial intelligence innovations aim to promote health equity, but this
I believe that artificial intelligence will provide many amazing solutions in the world of healthcare. The possibilities are endless from seamless diagnosis to virtual healthcare assistants to disease prevention and monitoring of health conditions. However, some challenges make the adoption of artificial intelligence in healthcare a difficult task. If governments of different countries, healthcare providers and organizations come together collectively to apply solutions that provide access to artificial intelligence in healthcare for everyone, the burden on healthcare workers will be reduced and patient health will improve. There will be an overall reduction in patient morbidity and mortality, indirectly improving work productivity and increasing the Gross Domestic Product. If these solutions are not applied, people from low and middle-income countries, minority groups, and the financially challenged may not get access to the several benefits that artificial intelligence tools provide in healthcare. Equity would be just a fancy word we say, just to make everything better when healthcare is becoming more difficult to access. My question is, “ What is it going to be?” “Is Artificial Intelligence in Healthcare A Ticking Time Bomb or A Timely Solution?” The answer is: it depends on us. Only time will tell.