اولین همایش بین المللی تحول خدمات سلامت: تلفیق مراقبت، درمان، بازتوانی و امیدبخشی

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کد مقاله 1069

عنوان The Role of Artificial Intelligence in Diagnosis and Treatment of Diseases: A Review Article

نویسندگان Neda Jalili - Hadi Haghgoo

چکیده Background: Early diagnosis of diseases is one of the main goals of health systems, which can reduce the potential harms of diseases . Artificial intelligence is the ability of a computer or robot to perform tasks that typically require human intelligence and judgment, and its emergence in today's world has improved the performance of healthcare systems . AI-based systems make it possible to identify suspected cases of diseases with minimal contact with healthcare personnel and monitor the treatment process . The aim of this review study is to investigate the role of artificial intelligence in the diagnosis and treatment of diseases. Method: This study is a review article conducted by searching reputable databases including PubMed, Scopus, Google Scholar, SID, and Science Direct in the time period from January 2016 to January 2026. The search was performed using keywords such as artificial intelligence, disease diagnosis, treatment, machine learning, and neural networks. Among the articles found, 5 articles related to the topic were selected and underwent content analysis. Finding: The findings of the reviewed studies showed that artificial intelligence has wide applications in disease diagnosis and prediction. In veterinary medicine, this technology has been used in areas such as diagnosis of common diseases, differential diagnosis, disease occurrence prediction, diagnostic imaging techniques, and clinical pathology . During the COVID-19 pandemic, artificial intelligence played an effective role in rapid diagnosis, monitoring of infected individuals, treatment development, research facilitation, prevention, and drug and vaccine design . In diagnosing hypertension, artificial intelligence algorithms have been able to predict and diagnose this disease with high accuracy . In diagnosing pulmonary tuberculosis, the Naive Bayes algorithm showed acceptable performance with 95.89% accuracy, 93.59% sensitivity, and 98.53% specificity, and the area under the receiver operating characteristic curve (AUC) was calculated as 98.91%, indicating the system's ability to assist in early diagnosis, especially in areas with limited access to laboratory resources . In diagnosing Alzheimer's disease from MRI images, the combined method of conditional random field and Inception deep neural network achieved 98.51% accuracy for two-class classification of Alzheimer's versus normal control and 93.41% accuracy for two-class classification of mild cognitive impairment versus normal control, showing an increase of 2.56% and 8.41% compared to rival methods, respectively . Conclusion: The role of artificial intelligence in disease diagnosis and treatment is multidimensional and vital. This technology can identify patterns beyond defined rules and analyze significant amounts of information. The application of artificial intelligence in early disease diagnosis, reduction of diagnostic errors, drug system management, reduction of healthcare personnel workload, and acceleration of the treatment process is effective. The development and implementation of artificial intelligence algorithms in health systems can be an effective step toward improving the quality of disease diagnosis and treatment. Keywords: Artificial Intelligence, Disease Diagnosis, Treatment

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