Diagnostic radiologists use various imaging techniques to diagnose diseases, these include: X-ray, Computed Tomography, magnetic resonance imaging, ultrasound. AI algorithms have a great ability to analyze image patterns and digital data, and in a study conducted in 2019, the readings of an autonomous AI model without the input of a radiologist were compared with the readings of 101 radiologists to analyze 2652 mammograms to detect cases of breast cancer, and the study found that AI was just as good at analyzing images as a radiologist. In another study conducted in 2023, artificial intelligence assistance in reading chest X-ray images improved the detection of abnormalities associated with pneumothorax by as much as 26%, and pulmonary nodules, which can be an early sign of a lung tumor, by as much as 9%. Soon, artificial intelligence is expected to become an essential assistant for radiologists. But in the distant future, the need for radiologists may decrease with the development of artificial intelligence and the emergence of high-precision instruments that can quickly analyze various medical images. You can find out more information about the role of artificial intelligence in the development of the field of medical image analysis in the article: How does artificial intelligence help in the development of the field of medical image analysis? 2-pathology:
Pathology involves making diagnoses by examining tissues, cells, and bodily fluids using laboratory instruments. Like radiology, AI-powered algorithms can analyze digital segments used in pathology, enhancing cancer detection, tumor classification, and biomarker estimation. A study conducted in 2022 showed that the artificial intelligence model developed to help diagnose tissue-related medical conditions significantly improved the diagnostic accuracy of mucosal soft tissue problems that pathologists find difficult to diagnose due to complex tissue interference. The accuracy of the artificial intelligence model reached 97% compared to 70% for pathologists, and the error rate decreased by 90%. In a study conducted in 2024, pathologists used a specially developed artificial intelligence model to help analyze thyroid samples taken with a fine needle (Thyroid Fine-Needle Aspiration Cytology), and found that it succeeded in analyzing samples by 95% compared to 89% for expert pathologists. The results of these studies indicate that artificial intelligence can increase the accuracy and speed of the work of pathologists, and with the advancement of artificial intelligence in the future, some of the work associated with the analysis of samples may become fully automated. 3-Dermatology:
The work of Dermatologists involves the assessment of rashes and other skin problems, and currently, artificial intelligence models trained on large datasets of skin images can identify cases of skin cancer, diagnose chronic skin problems. A recent study found that the use of artificial intelligence has significantly improved the accuracy of dermatologists in identifying melanoma (cancer) and birthmarks (moles) from skin images, and the accuracy has increased from 65% to 73%. Another study found that artificial intelligence improved the accuracy of non-expert doctors in diagnosing skin problems, with an accuracy rate of 54% for the group assisted by artificial intelligence compared to 44% for the group that did not receive assistance. Artificial intelligence algorithms are used to diagnose skin diseases and will continue to improve, and some AI-powered medical applications, such as Skin Vision and Mole Mapper, can diagnose skin conditions without human intervention. The expanded use of artificial intelligence in Dermatology suggests the possibility of shifting the task of diagnosing some skin conditions to non-specialists as well as directly to patients. 4-Internal Medicine:
Internal Medicine includes cardiologists, endocrinologists, gastroenterologists, rheumatologists, infectious disease doctors, and, in the future, consulting doctors in these specialties may increasingly rely on artificial intelligence that can help interpret the results of analyses, ECGs, and make data-based recommendations. Given the various effects that artificial intelligence technology causes in the medical fields, it is expected that this technology will affect non-surgical work faster than surgical work; artificial intelligence is currently used in medicine to analyze data and help diagnose, and it is unlikely that an artificial intelligence robot will work independently in the surgical field soon.
The speed of changes in these specialties is unknown, but it is known that the healthcare industry is noticeably slow to adopt new innovations due to the potential impacts on patients ' lives. There will also be resistance from competent doctors, especially when the adoption of artificial intelligence affects the remuneration that doctors receive. However, considering the possible future of these specialties is important for medical students who are thinking about choosing the right medical specialty for themselves, at a time when artificial intelligence tools are beginning to change the medical field.