Utility and efficacy of bone marrow examination in the diagnosis of haematological and non-haematological disorders.

Agale,; Mishra, S. R.; Kinake,; Rathod,; Bijwe,; DCunha,; Sharma,

doi:10.5455/ijmrcr.utility-bone-marrow-examination

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“…Smear review in bone marrow examination is frequently used for diagnosing infiltrated hematologic disorders and helps differentiate between the underlying causes. PBS and BMS examinations are essential to confirm a clinically suspected disease and to uncover a previously unsuspected diagnosis [ 17 ]. Depending on the circumstances, peripheral blood, BMAs, and trephine biopsy are possible samples to use for analyzing the cytomorphology of blood cells as well as their pattern of distribution [ 18 ].…”

Section: Current Applications Of Ai In Hematologic Cytologymentioning

confidence: 99%

Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders

Gedefaw

Liu

et al. 2023

Cells

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Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the development of computational programs that can mimic human intelligence. In particular, machine learning and deep learning models have enabled the identification and grouping of patterns within data, leading to the development of AI systems that have been applied in various areas of hematology, including digital pathology, alpha thalassemia patient screening, cytogenetics, immunophenotyping, and sequencing. These AI-assisted methods have shown promise in improving diagnostic accuracy and efficiency, identifying novel biomarkers, and predicting treatment outcomes. However, limitations such as limited databases, lack of validation and standardization, systematic errors, and bias prevent AI from completely replacing manual diagnosis in hematology. In addition, the processing of large amounts of patient data and personal information by AI poses potential data privacy issues, necessitating the development of regulations to evaluate AI systems and address ethical concerns in clinical AI systems. Nonetheless, with continued research and development, AI has the potential to revolutionize the field of hematology and improve patient outcomes. To fully realize this potential, however, the challenges facing AI in hematology must be addressed and overcome.

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Section: Current Applications Of Ai In Hematologic Cytologymentioning

confidence: 99%