Artificial intelligence (AI) is indeed here and has been rapidly advancing in recent years. From virtual assistants, self-driving cars, fraud detection algorithms, robotics and more. As such, artificial intelligence has also made its way into the doctor’s office and has the potential to revolutionize the health care system in a number of ways.
Machine learning can analyze algorithms and large data sets, identify patterns, and make predictions, assisting doctors in making more accurate diagnoses and treatments.
In the last 10 years, medical capabilities have advanced. Personalized medicine, tailoring medical treatments and interventions to individual patients based on their unique genetic makeup, lifestyle factors and environmental influences, is the standard of care.
AI can help by considering individual patient characteristics, such as genetic profiles, medical history and even lifestyle factors. By analyzing a wide range of data, AI systems can generate personalized recommendations to include not only medications but additional screening testing and lifestyle modifications to promote overall wellness.
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AI is also able to help with predictive analysis. In medicine, we try to prevent the disease before it happens or diagnose it at its earliest stage when it’s easier to treat. Currently, there are many risk stratification models being used to determine the risk of developing illness, all with their own strengths and limitations. AI is able to assist in risk stratification with utilizing multiple risk models and compiling them into a single, actionable model that may be able to provide a more accurate prediction of future disease.
As a radiologist, the emergence of AI in health care is not new to me. We have been utilizing some form of machine learning with image enhancement and interpretation for the last decade. The AI algorithms are able to assist in improving image quality and with detecting anomalies on various imaging modalities (CT scans, X-rays, mammograms, ultrasound, MRI). The hope is that AI systems will improve accuracy, decrease false positive interpretations and improve overall efficiency. However the need to validate the AI algorithms with rigorous testing is crucial.
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But it’s not only the patients that may potentially benefit from AI in health care.
Physicians are burnt out. The current health care system, filled with high emotional intensity, increased workload and decreasing reimbursements, has resulted in over 53% of doctors reporting burnout in 2023. One of the leading causes of burnout is the administrative burdens doctors are tasked with.
If AI were able to automate such tasks like data entry, billing, scheduling, ordering and even email response, this would allow the physician more time with the patient and their families and less time at the computer. If the physician is unhealthy, they cannot provide best medical care so making sure the health care workers are OK is also critical for optimal patient care.
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It will take time before doctor’s fully trust machine learning with their patients’ lives so the widespread adaptation of AI has been slow and rightfully so.
The future of medicine is an exciting and evolving field with new advancements in technology, scientific research and innovative approaches being produced every day.
Artificial intelligence has a place in health care and can improve many of the organizational deficiencies. However, the health care system is notorious for implementing lower cost, higher efficiency systems before proven beneficial for the individual. Caution must be taken when implementing AI into various aspects of the medical system to ensure patients are still receiving best practices with human consideration because people are not robots. They are human.
AI holds significant potential, but it should not replace the human physician.
AI should be viewed as a tool to assist a physician by removing tedious administrative tasks, enhancing diagnostic capability, and improving patient outcomes. Ethical considerations, data privacy, and the crucial need for human oversight remain essential in the integration of AI in health care.
