The advancement of artificial intelligence (AI) has revolutionized the healthcare industry, enabling medical professionals to provide better patient care and faster diagnosis. AI algorithms can process vast amounts of medical data to identify patterns and anomalies that are difficult for humans to detect. Doctors worldwide are using this technology to improve the accuracy of diagnoses and optimize treatment plans.
Artificial intelligence impacts how medical care is administered in doctors’ offices and hospitals. These changes can already be seen and will continue to evolve as AI continues to grow and evolve.
At Mayo Clinic’s cardiology department, doctors use an artificial intelligence program to help detect new heart problems. Elsewhere, a group of primary-care doctors uses it to help identify an eye condition that can lead to blindness. Several hospitals are using it to catch patients at risk for sepsis.
Doctors don’t completely rely on AI tools to diagnose patients despite using the technology for paperwork and report testing, as algorithms are developed to identify people at risk of pervasive conditions or diseases.
Using AI, some doctors’ diagnoses can now routinely be achieved earlier than they typically would without its use. Additionally, on many occasions, with its utilization, their assignment of an individual prognosis is more precise and accurate.
AI promises much in healthcare, but physicians are cautious because of emerging and potentially biased technology. Research confirms that some patients can be disadvantaged when AI inputs shape care management.
Previous attempts to bet big on the possibility that AI would revolutionize healthcare, like IBM’s Watson Health initiative, have turned out to be disappointments or, at least for now, premature.
“I don’t think we are at a place where we can just let algorithms run and make the decisions,”
Dr. Michael Pencina, Director of Duke AI Health, focuses on activities that promote the utilization of AI and machine learning at Duke University’s School of Medicine through research. AI algorithms gain data as inputs, advancing strength and accuracy in return outputs, thus growing and developing continuously over time.
John Halamka, president of the Mayo Clinic Platform, has identified a challenge in developing AI technology. According to Halifax, one issue lies in how the technology is developed, and the Mayo Clinic Platform is working with health IT companies to create AI tools to address these concerns.
The algorithms use information, often from electronic health records, such as demographic and health history, vital signs, and labs, to determine whether a patient might have a certain health issue.
Doctors report back on the accuracy of assessment, leading to enhanced performance of the technology as more it is used. Nonetheless, an algorithm developed for a particular base (e.g., patients in Minnesota) likely would only be sufficient with alteration when implemented among those with drastically different population characteristics.
AI in healthcare can lead to racial bias that adversely affects patient care, as evidenced by a 2019 Science study. To reduce inequity and create fair criteria, last year, tech and healthcare professionals united to draft standards for the ethical usage of AI in this context.
Many companies are researching AI and developing products for doctors and health systems. Nevertheless, the transformative potential of such technology has yet to manifest in Medical practices meaningfully.
The use of AI in healthcare is rapidly expanding, and doctors are finding innovative ways to incorporate this technology into their practices. With the ability to analyze large amounts of medical data quickly and accurately, AI algorithms have the potential to revolutionize the diagnosis and treatment of diseases.
Although AI technology is not a replacement for human doctors, it has the potential to supplement their expertise and enhance patient care. By improving the accuracy and speed of diagnoses, doctors can provide patients with more personalized and effective treatments.
Source: WSJ
