Abstract
This research paper explores the essential role of clinical blood analysis in the identification and diagnosis of various diseases. Blood tests, due to their non-invasive nature and rich diagnostic potential, are widely used to evaluate physiological functions, detect pathologies, and monitor disease progression. The paper examines traditional diagnostic methods such as complete blood count and biochemical analyses, as well as more advanced techniques including molecular diagnostics and artificial intelligence-supported interpretations. By comparing different testing approaches and evaluating their clinical utility, the study highlights both the strengths and limitations of current diagnostic practices. Furthermore, it discusses challenges such as preanalytical errors, variability in test results, and unequal access to laboratory services in low-resource settings. The paper concludes that clinical blood analysis, if accurately performed and interpreted, is a cornerstone of modern diagnostics and plays a vital role in improving patient care and treatment outcomes.
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