Artificial Intelligence in pathology: current applications, limitations, and future directions

Assessing Public Knowledge and Acceptance of Using Artificial Intelligence Doctors as a Partial Alternative to Human Doctors in Saudi Arabia: A Cross-Sectional Study

Objective To assess the public acceptance of using artificial intelligence (AI) doctors to diagnose and treat patients as a partial alternative to human physicians in Saudi Arabia. Methodology An observational cross-sectional study was conducted from January to March 2024. A link to an online questionnaire was distributed through social media applications to citizens and residents aged 18 years and older across various regions in Saudi Arabia. The sample size was calculated using the Raosoft online survey size calculator, which estimated that the minimum sample size should be 385. Results Of the 386 participants surveyed, 85.8% reported being aware of AI, and 47.9% reported having some knowledge about different AI fields in daily life. However, almost one-third (32.9%) reported a lack of knowledge about the use of AI in healthcare. In terms of acceptance, 52.3% of respondents indicated they felt comfortable with the use of AI tools as partial alternatives to human doctors, and 30.8% believed AI is useful in the field of health. The most common concern (63.7%) about the use of AI tools accessible to patients was the difficulty of describing symptoms using these tools. Conclusion The findings of this study provide valuable insights into the public's knowledge and acceptance of AI in medicine within the Saudi Arabian context. Overall, this study underscores the importance of proactively addressing the public's concerns and knowledge gaps regarding AI in healthcare. By fostering greater understanding and acceptance, healthcare stakeholders can better harness the potential of AI to improve patient outcomes and enhance the efficiency of medical services in Saudi Arabia.

ChatGPT as an aid for pathological diagnosis of cancer

Diagnostic workup of cancer patients is highly reliant on the science of pathology using cytopathology, histopathology, and other ancillary techniques like immunohistochemistry and molecular cytogenetics. Data processing and learning by means of artificial intelligence (AI) has become a spearhead for the advancement of medicine, with pathology and laboratory medicine being no exceptions. ChatGPT, an artificial intelligence (AI)-based chatbot, that was recently launched by OpenAI, is currently a talk of the town, and its role in cancer diagnosis is also being explored meticulously. Pathology workflow by integration of digital slides, implementation of advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond a microscopic slide and enables effective integration, assimilation, and utilization of knowledge that is beyond human limits and boundaries. Despite of it's numerous advantages in the pathological diagnosis of cancer, it comes with several challenges like integration of digital slides with input language parameters, problems of bias, and legal issues which have to be addressed and worked up soon so that we as a pathologists diagnosing malignancies are on the same band wagon and don't miss the train.