Importance: Artificial intelligence has the potential to impact the medical field significantly. However, faulty diagnoses remain a major concern, potentially leading to higher medical costs, patient distress, and distrust in the healthcare system.

Objectives: This secondary research study examines the relationship between the integration of AI technology and diagnostic outcomes within medical imaging. 

Methods: The two-month study utilized PubMed, ELSEVIER, National Institute of Health, and Google Scholar to collect peer-reviewed, full-text articles (2015–2025). Randomized controlled trials were included, while meta-analyses and editorials were excluded. A thematic analysis explored AI’s role in supporting diagnoses, the limitations of complete automation, and the impact of software quality and training on patient outcomes.

Results: Fifteen studies were analyzed. Findings indicated how AI served as a diagnostic aid for medical practitioners. Additionally, AI model performance was heavily influenced by the quality of training, data input, and model development. 

Conclusion: AI technology holds great potential for enhancing medical imaging diagnosis, but it is unsuitable for independent use. Continued advancements in AI software and ethical considerations, including patient emotional distress and medical distrust, should be investigated before integrating AI into clinical practice. Furthermore, outcomes of long-term collaboration between AI and medical professionals should be investigated further.