The word “artificial intelligence” is currently ubiquitous, and its impact has been dramatically increased in recent years, and its effects have been felt in healthcare and many other employment departments. In healthcare, artificial intelligence and AI can make drug discovery faster and cheaper and improve diagnosis and treatment. How can AI need to keep the privacy of the patient and how can it be used fairly? How can AI improve patient care, increase efficiency, and reduce costs? These are questions that require a thoughtful discussion.
Dr. Koushik Kasanagottu, a public health specialist and clinical professor at the Faculty of Medicine at the Faculty of Medicine of the UC Riverside Medical School, is working on questions related to AI in Q & A in the following Q & A. Before participating in the UCR as a community -based teacher, Casanagotu was a Fellow of Harvard University School of Medicine and the U.S. -House, which improved medical policy and innovation expertise. He is a founding member and doctor advisor of Docaide, a startup of healthcare AI focusing on clinical decision -making changes.
Q: How is AI transformed?
AI is growing exponentially in the healthcare industry. Healthcare has been significantly transformed by rationalizing management tasks and improving documents. In my own practice, I use AI wrestlers every day to document the visit of patients. This allows you to focus on large -scale notebooks, improve patient experience, and spend more time facing patients, rather than focusing on the quality of encounters. However, these tools still require monitoring of clinicians to ensure accuracy and quality. In the future, the AI tools will strengthen decision -making, support clinical inference, and reduce diagnostic errors.
Q: How do doctors and other medical staff use AI? How does the patient use it?
Doctors and medical staff are more and more integrated with AI tools in various care aspects. This is just the beginning. As you learn more about technology and its use, you can integrate it into clinical care as a clinical decision -making support tool. However, integration is risky and needs to monitor a clinician.
Q: What are the possibilities of AI in the medical field? How does it define the future?
Since we continue to develop and improve AI -driven tools such as SCRIBING Software and Clinical Decision Support, we can analyze images, predict the progress of the disease, and recommend treatment plans based on vast datasets. It will be. In the future, AI may be an essential part of both clinical decision -making and patient management, especially in areas where services are inadequate, in real time support and reduce medical burden. I will do it. AI can play an important role in reducing medical gaps by providing expert -level care in a remote area where experts are missing. However, there is a risk. AI is as good as training data, so the dataset has a sufficient service and an alienated group, which is underestimated to obtain bias and inaccurate.
Q: What is the best way to adjust AI in medicine?
To regulate medical AI, it is necessary to balance innovation and ensure patient safety. It is indispensable for regulatory agencies such as the Food and Pharmaceutical Bureau (FDA) to establish a clear and standardized guideline of AI verification, and thoroughly tested the accuracy and safety before these technologies develop in a clinical environment. I will do it. You also need a series of criteria that must be met before new AI products are integrated into clinical care. FDA is currently proposing some regulatory frameworks to ensure safe development of AI products in clinical products. The continuous monitoring of the AI system after deployment is also important to evaluate long -term validity and reduce unexpected risks. You need to test and monitor accuracy through the use of AI that exceeds the satisfaction score of patients and providers.
Q: How can AI support illness diagnosis and risk prevention?
AI can play a very important role in both the diagnosis of the disease and the prediction of the patient’s future health risk. For example, AI algorithms can analyze patient data. Identify the pattern of the lab, imaging, and genetic information. We propose early intervention in chronic diseases such as diabetes and heart disease. In this field, there are some startups and technology companies that have been innovated in this field to provide predictive and clinical decisions. According to Lancet research, AI -based tools improve early cancer detection by analyzing medical imaging with remarkable accuracy, and clinicians are faster and more treated. It has been shown to be useful.
Q: Is AI replacing medical providers? Which job of health care is the most vulnerable to AI?
AI is not an alternative to doctors, but by processing repeated tasks and enhancing clinical decisions, you will definitely change the medical practice method. For example, AI supports imaging diagnostic accuracy, supports daily data entry, and supports treatment plans. This allows doctors to concentrate on direct patient care. However, human elements of patient care, empathy, and clinical judgment are always indispensable.
Q: What is the risk of using AI in medicine? What are ethical concerns?
There are important ethical concerns about AI. I am deeply concerned about how the privacy of data, especially the bias of algorithms in the population, and the dependence on this technology will worsen the health gap. In particular, the AI system can make the existing bias of the trained data inadvertently permanently permanently, and can lead to a gap in care. One of the ongoing ethical issues is to guarantee that AI tools are developed and tested in a way to represent a variety of groups.
Q: Is there a patient’s safety risk? How are your privacy concerns?
Yes, the use of AI in healthcare has potential patient safety and privacy concerns. If the AI system creates incorrect recommendations and can lead to delay in misdiagnosis or treatment, safety risks may occur. For example, AI systems may overlook a rare state or flag the problem of benign as a serious problem that affects clinical decisions. In terms of privacy, AI depends on a huge amount of patient data, raising concerns about data violation or misuse. It is important that the AI system complies with strict privacy methods such as HIPAA, and guarantees that the data used for training these systems is anonymized and ethically procured.
Header Image Credit: Victor Perry, California Riverside.
