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Artificial intelligence has come a long way in advancing business processes and improving medical services. One area of medical science where AI shows a lot of potential is diagnostics. Depending on the disease, it can take doctors a long time to diagnose an illness. It can take as long as four to nine years for some rare diseases to receive an accurate diagnosis. However, AI may be the next step in making diagnoses faster and more accurate.
Benefits of Using AI in Medical Diagnostics
Artificial intelligence has several benefits that can be utilized in medical diagnostics. Some of these include:
1. Artificial intelligence can interpret large data sets to find patterns much faster than human doctors can.
2. AI, when programmed correctly, can be less susceptible to bias.
3. Diagnoses made by AI can be more accurate.
According to a study by the Journal of the National Cancer Institute, AI diagnosis was found to achieve 95% confidence intervals in tests to detect cancer. In fact, the AI had an AUC higher than 61.4% of radiologists in the study.
Artificial intelligence is much better at interpreting large quantities of medical data sets than humans are. With many patients on waiting lists for organ transplants, surgeries, and other treatments due to high demand, AI can help speed up this process by taking the burden off doctors to perform tasks like diagnostics in many cases.
This doesn’t mean that AI will completely replace human diagnosis. Instead, AI can weed through large numbers of patients to make initial diagnoses and refer a smaller set of high-risk patients to doctors for a second look.
Use Cases for Artificial Intelligence in Medical Diagnostics:
There are a number of use-cases where AI can greatly improve medical diagnostics. Some of the most promising use-cases include cancer detection and early dementia prediction.
AI for Cancer Detection
This is one of the most important use-cases that is receiving some of the greatest attention. One way to detect cancer is with Whole Slide Imaging (WSI) from histology results. These slides have gigantic resolutions that are time-consuming to analyze by humans. However, artificial intelligence can perform the task in a fraction of the time. This is the basis for AI image analysis for cancer detection. An AI algorithm can automatically recognize points of interest in WSI images that may indicate malignant cells.
AI for Early Dementia Prediction
Another use case is AI for dementia diagnosis. If the disease can be predicted in advance, its effects can be mitigated with proper treatment. The earlier that diagnosis is completed, the better. By analyzing communicative and reasoning data from patients, AI can predict the likelihood that a patient will develop dementia within a set period of time.
AI-based speech analysis is a method that can be used to assist with this analysis. Using recordings of neuropsychological tests, doctors can detect early signs of dementia long before damage to brain cells occurs. For example, symptoms such as difficulty in thinking, trouble concentrating, and memory loss may be signs of the disease, and people who have them need further diagnosis.
Future of AI in Medical Diagnostics
Global healthcare systems depend on accurate diagnosis. BMJ Quality and Safety Journal states that 5% of United States outpatient cases are misdiagnosed. This can result in a great deal of harm to patients, either because they miss out on necessary treatment or receive unnecessary treatment. In either case, serious patient harm is possible. Artificial intelligence can be critical toward minimizing this issue. When human doctors team up with AI algorithms to enhance their work, medical diagnostics can be more efficient, accurate, and easier to obtain.
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