Artificial Intelligence and Choosing a Medical Specialization
Artificial intelligence is being used in almost every field, including medicine; it is increasingly being used in medical institutions, and can enhance or completely perform some of the tasks performed by doctors. Therefore, medical students should consider how artificial intelligence can change the way doctors work, and which medical specialties are most affected by the development of artificial intelligence before choosing the medical specialty they want to study.
This is important for medical students given the significant investment of time and effort required to train in their chosen specialty, as the development of AI raises concerns about the potential for some medical specialties to be abandoned and AI tools to work instead of doctors, or as a primary assistant who takes on most medical tasks, which would impact doctors’ salaries.
Similar concerns arose about the possibility of some jobs disappearing with the Industrial Revolution of the period from 1760 to 1840. There was a concern that workers would be left behind as new industrial machines were invented. Some jobs did disappear completely, but new jobs emerged because people were needed to maintain and repair machines.
The AI revolution is expected to follow a similar path, but much faster. As AI begins to change medical practice, it may also change the needs of the medical workforce in different ways.
Below we will mention some medical specialties in which artificial intelligence may be used extensively and perform a large part of doctors’ tasks in the future:
1- Diagnostic Radiology Specialization:
Diagnostic radiologists use a variety of imaging techniques to diagnose diseases, including: X-rays, computed tomography, magnetic resonance imaging, and ultrasound.
AI algorithms have a great ability to analyze patterns in images and digital data. In a 2019 study, the readings of an independent AI model without radiologist input were compared to those of 101 radiologists analyzing 2,652 mammograms to detect breast cancer. The study found that AI was just as good at analyzing the images as radiologists.
In another 2023 study , AI-assisted reading of chest X-rays improved detection of abnormalities associated with pneumothorax by 26%, and pulmonary nodules, which can be an early sign of a lung tumor, by 9%.
In the near future, AI is expected to become an essential assistant to radiologists. But in the distant future, the need for radiologists may decrease as AI advances and high-precision tools emerge that can quickly analyze different medical images.
You can learn more about the role of artificial intelligence in developing the field of medical image analysis in the article: “ How does artificial intelligence help develop the field of medical image analysis? ”
2- Pathology:
Pathology involves making diagnoses by examining tissues, cells, and bodily fluids using laboratory tools. Like radiology, AI-powered algorithms can analyze digital slides used in pathology, enhancing cancer detection, tumor classification, and biomarker estimation.
A 2022 study showed that an AI model developed to help diagnose tissue-related medical conditions significantly improved the diagnostic accuracy of mucosal soft tissue problems that pathologists struggle to diagnose due to complex histological overlap. The AI model was 97% accurate compared to 70% for pathologists, and the error rate was reduced by 90%.
The results of these studies suggest that AI can increase the accuracy and speed of pathologists' work, and as AI advances in the future, some of the work associated with sample analysis may become fully automated.
3- Dermatology:
Dermatologists' work involves evaluating rashes and other skin problems, and currently, AI models trained on large datasets of skin images can identify skin cancers and diagnose chronic skin problems.
A recent study found that the use of artificial intelligence significantly improved dermatologists’ accuracy in identifying melanoma (cancer) and moles from skin images, increasing accuracy from 65% to 73%.
Another study found that AI improved the accuracy of non-expert doctors in diagnosing skin problems by 54% for the group assisted by AI versus 44% for the group without it.
AI algorithms are being used to diagnose skin conditions and will continue to improve, with some AI-powered medical applications such as Skin Vision and Mole Mapper able to diagnose skin conditions without human intervention.
The expanded use of AI in dermatology suggests that the task of diagnosing some skin conditions could be shifted to non-specialists as well as directly to patients.
4- Internal medicine:
Internal medicine includes cardiologists, endocrinologists, gastroenterologists, rheumatologists, and infectious disease physicians, and in the future, consultant physicians in these specialties may increasingly rely on AI that can help interpret lab results, ECGs, and make data-driven recommendations.
Conclusion:
Given the various impacts AI technology has on medical fields, it is expected to impact non-surgical work more quickly than surgical work. AI in medicine is currently used to analyze data and assist in diagnosis, and it is unlikely that an AI robot in the surgical field will operate autonomously in the near future.
It is not known how quickly these changes will occur in these specialties, but it is known that the healthcare industry is notoriously slow to adopt new innovations because of the potential impact on patients’ lives. There will also be resistance from specialist physicians, especially when the adoption of AI affects the way doctors are paid.
However, considering the potential future of these specialties is important for medical students considering which medical specialty is right for them, at a time when artificial intelligence tools are beginning to transform the medical field.