How Could Doctors Use AI?

AI is everywhere, so it is no surprise that it has entered the medical field. Doctors have begun to leverage AI to assist in: 

• Improving the patient diagnosis process

• Enhancing drug discovery and development

• Simplifying and improving doctor-patient communication

• Summarizing published medical articles and studies

• Transcribing documents and notes

• Treating patients remotely

Certain AI algorithms are nearly as good as human doctors in specific ways. Recent models of ChatGPT can now even pass the United States Medical Licensing Examination (USMLE). However, while some experts in the field argue that AI may replace doctors when it comes to certain tasks, particularly diagnostic and administrative tasks, human-AI cooperation is more likely than AI entirely replacing doctors. So, how could doctors use AI to improve the practice of medicine? 

AI in diagnostics

You can use AI in diagnostics. Diagnosing a patient is a complex process where you must collect their medical history, the nature of their complaint, and their demographic information, then compare that information against your knowledge of diseases. After making a preliminary diagnosis, you must often make a differential diagnosis because some diseases resemble each other in terms of symptom presentation but have widely varying treatment modalities. AI algorithms, such as chatbots that provide generally accurate and remarkably human-like answers to prompts, are now so advanced and reliable that they have become valuable reference tools. You can embrace these tools to help quickly provide the most accurate diagnoses to your patients.

You can use AI to help simplify and improve your diagnostic process. A Stanford University study found that AI allowed doctors to accurately diagnose skin cancer in patients approximately 5 percent more often than they had previously been able to do unassisted [1]. 

Personalized medicine

You can use AI to develop treatment plans for patients. An AI algorithm can analyze your patients’ data, including their medical history, lifestyle, and genetic information, and compare it against the treatment responses of similar patients to create personalized treatment plans for your patients.

You can use AI to provide all-day care for your patients every day of the year. An AI algorithm can be there for your patients when you cannot, answering their questions, addressing their concerns, and adjusting their treatment plans based on emerging symptoms or situations. 

You can use AI for patient education. Because medicine is a highly technical and complex discipline, patients do not always have a meaningful grasp of it, so you can leverage AI to write letters to your patients explaining the nature of their condition, how you diagnosed it, why you feel that a specific treatment is necessary, and how they can take their medications. 

Predictive analytics in patient care

You can use predictive analytics to improve patient care. AI has proven quite good at predicting the chances of a patient developing a specific medical condition based on their history, demographics, and lifestyle factors, for example, diabetes in patients with a family history of diabetes or congestive heart failure in patients with coronary artery disease. By accurately predicting whether a patient will develop a medical condition, AI allows you to work with them to better prepare for the potentiality of them developing the condition and change the trajectory of their condition by managing their lifestyle factors and ensuring adherence to preventative treatment plans. 

You can use earlier and more accurate AI diagnosis to lead to positive patient outcomes such as: 

• Increased treatment adherence

• Improved risk factor analysis 

• Enhanced prognostic analysis

• Faster screening

Ensuring that your patients receive an accurate diagnosis the first time they visit a health care facility and adhere to their prescribed treatment plan will make them more likely to recover quickly, experience less progression in chronic disease symptoms, and avoid readmittance to the hospital. 

Administrative efficiency

You can use AI to improve your administrative efficiency. You can incorporate AI into your day to streamline non-medical administrative tasks, such as scheduling, billing, and patient records management. In addition, you can utilize AI-based automatic speech recognition (ASR) technology. This transcription algorithm takes the verbal notes that you record following your patient visits and turns them into text, which the patient records management system then places in a patient’s file. This technology reduces the time you spend completing administrative tasks so you can focus more fully on optimizing patient outcomes. 

You can use AI to reduce burnout. The American Medical Association (AMA) reported that 48.2 percent of doctors regularly experience at least one symptom of burnout [2]. Using AI to automate your administrative tasks can decrease your chances of burnout, improve your mental and physical well-being, and increase your productivity and long-term success.

Enhanced decision-making

You can use AI to help with decision-making and avoid making critical errors such as: 

• Demonstrating environmental bias, including treating patients for common ailments at a particular place and time of year instead of testing for other conditions that present with similar symptoms

• Showing racial bias, including treating patients of various races differently, either intentionally or unintentionally

• Taking shortcuts, including not learning how to apply the knowledge about symptoms that you learned in medical school

• Communicating ineffectively and causing mistrust, including inspiring patients to withhold information if they feel you are cold or uncompassionate

You can use AI to take some of the guesswork out of your decision-making because it can accurately recommend tests and address patient questions. You can also potentially use AI to administer anesthesia to patients automatically before specific medical procedures. 

AI in drug discovery and development

Currently, the drug development process, from conception to market availability, takes an average of 9.1 years [3] and costs an average of $2.6 billion [4]. 

Those numbers could continue to climb. Clinical research, which has long been the standard for the drug development process, is taking longer than it ever has due to: 

• Complex protocols

• Globalized drug trials

• Intricate drugs

• Supply chain challenges

You can use AI in drug discovery and development to speed up the process and reduce costs. Utilizing AI to examine enormous data sets helps identify the best drug candidates for clinical trial testing and predict their effectiveness, decreasing your trial selection time and related costs. 

You can use AI to analyze large data sets and compare multiple sets against one another to help develop new drug designs and beneficial drug combinations. 

You can use AI to get drugs to patients more quickly. The lengthy drug development process burdens undertreated patients, so you can use AI to expedite the drug development, approval, and marketing processes. By leveraging AI, you might be able to get drugs to the first-in-human (FIH) trial phase 40 percent faster than by using traditional methods [5]. 

Learn more about AI in health care with Coursera

Doctors can use AI to diagnose patients, provide personalized treatment plans, predict diseases, perform administrative tasks, boost decision-making, and streamline drug discovery and development to improve patient outcomes. 

To learn more about the use of AI in medicine, consider completing DeepLearning.AI’s AI for Medicine Specialization on Coursera, a three-course series designed to help you use AI to diagnose diseases, estimate treatment effects, and automate tasks. For a more detailed investigation of AI in medicine, consider completing Stanford University’s AI in Healthcare Specialization on Coursera, a five-course series designed to help you identify areas for AI implementation, analyze how AI affects patient care and safety, and apply AI in a health care setting.