Aims/Background: The growing integration of artificial intelligence (AI) into clinical medicine has opened new possibilities for enhancing diagnostic accuracy, therapeutic decision-making, and biomedical innovation across several domains. This review is aimed to evaluate the clinical applications of AI across five key domains of medicine: diagnostic imaging, clinical decision support systems (CDSS), surgery, pathology, and drug discovery, highlighting achievements, limitations, and future directions. Methods: A comprehensive PubMed search was performed without language or publication date restrictions, combining Medical Subject Headings (MeSH) and free-text keywords for AI with domain-specific terms. The search yielded 2047 records, of which 243 duplicates were removed, leaving 1804 unique studies. After screening titles and abstracts, 1482 records were excluded due to irrelevance, preclinical scope, or lack of patient-level outcomes. Full-text review of 322 articles led to the exclusion of 172 studies (no clinical validation or outcomes, n = 64; methodological studies, n = 43; preclinical and in vitro-only, n = 39; conference abstracts without peer-reviewed full text, n = 26). Ultimately, 150 studies met inclusion criteria and were analyzed qualitatively. Data extraction focused on study context, AI technique, dataset characteristics, comparator benchmarks, and reported outcomes, such as diagnostic accuracy, area under the curve (AUC), efficiency, and clinical improvements. Results: AI demonstrated strong performance in diagnostic imaging, achieving expert-level accuracy in tasks such as cancer detection (AUC up to 0.94). CDSS showed promise in predicting adverse events (sepsis, atrial fibrillation), though real-world outcome evidence was mixed. In surgery, AI enhanced intraoperative guidance and risk stratification. Pathology benefited from AI-assisted diagnosis and molecular inference from histology. AI also accelerated drug discovery through protein structure prediction and virtual screening. However, challenges included limited explainability, data bias, lack of prospective trials, and regulatory hurdles. Conclusions: AI is transforming clinical medicine, offering improved accuracy, efficiency, and discovery. Yet, its integration into routine care demands rigorous validation, ethical oversight, and human-AI collaboration. Continued interdisciplinary efforts will be essential to translate these innovations into safe and effective patient-centered care.

Melatonin is known to reduce detrimental effects of free radicals by stimulating antioxidant enzymes; however, its role has not been studied in 6-hydroxydopamine (6-OHDA)-induced rat model of Parkinson's disease (PD). Therefore, we aimed to elucidate the effects of melatonin on motor activity and oxidative stress parameters in 6-OHDA-induced rat model of PD. Three-month-old male Wistar rats were divided into 5 groups: vehicle (V), melatonin-treated (M), 6-OHDA-injected (6-OHDA), 6-OHDA-injected + melatonin-treated (6-OHDA-Mel), and melatonin-treated + 6-OHDA-injected (Mel-6-OHDA) group. Melatonin was administered intraperitoneally at a dose of 10 mg/kg/day for 30 days in M and Mel-6-OHDA groups, for 7 days in 6-OHDA-Mel group. Rats received a unilateral stereotaxic injection of 6-OHDA into the right medial forebrain bundle. The 6-OHDA-Mel group started receiving melatonin when experimental PD was created and the treatment was continued for 7 days. In the Mel-6-OHDA group, experimental PD was created on the 23rd day of melatonin treatment and continued for the remaining 7 days. Locomotor activity decreased in 6-OHDA group compared with that in vehicle group; however, melatonin treatment did not improve this impairment. 6-OHDA injection caused an obvious reduction in tyrosine-hydroxylase-positive dopaminergic neuron viability as determined by immunohistochemistry. Melatonin supplementation decreased dopaminergic neuron death in 6-OHDA-Mel and Mel-6-OHDA groups compared with that in 6-OHDA group. Biochemical analysis confirmed the beneficial effects of melatonin displaying higher superoxide dismutase, catalase, and glutathione peroxidase activities and lower lipid peroxidation in substantia nigra samples in comparison to non-treated 6-OHDA group. Starting melatonin treatment before creating experimental PD was more effective on observed changes.