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Role of Machine Learning in Liquid Biopsy of Brain Tumours.
Javed, Zanib; Bakhshi, Saqib Kamran; Khan, Saad Akhtar; Shamim, Muhammad Shahzad.
Afiliación
  • Javed Z; Section of Neurosurgery, Department of Surgery, Aga Khan University, Karachi, Pakistan.
  • Bakhshi SK; Section of Neurosurgery, Department of Surgery, Aga Khan University, Karachi, Pakistan.
  • Khan SA; Section of Neurosurgery, Department of Surgery, Aga Khan University, Karachi, Pakistan.
  • Shamim MS; Section of Neurosurgery, Department of Surgery, Aga Khan University, Karachi, Pakistan.
J Pak Med Assoc ; 74(6): 1194-1196, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38949002
ABSTRACT
Liquid biopsy has multiple benefits and is used extensively in other fields of oncology, but its role in neuro-oncology has been limited so far. Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. Large and complex amounts of data from liquid biopsy can be simplified by machine learning using various algorithms. By using this technique, we can diagnose brain tumours and differentiate low versus highgrade glioma and true progression from pseudo-progression. The potential of liquid biopsy in brain tumours has not been extensively studied, but it has a bright future in the coming years. Here, we present a literature review on the role of machine learning in liquid biopsy of brain tumours.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Aprendizaje Automático / Células Neoplásicas Circulantes Límite: Humans Idioma: En Revista: J Pak Med Assoc Año: 2024 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Pakistán

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Aprendizaje Automático / Células Neoplásicas Circulantes Límite: Humans Idioma: En Revista: J Pak Med Assoc Año: 2024 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Pakistán