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Transforming breast cancer care: harnessing the power of artificial intelligence and imaging for predicting pathological complete response. a narrative review.
Shaikh, Kulsoom; Mooghal, Mehwish; Ameen, Abdullah; Khan, Wajiha; Zeeshan, Sana; Vohra, Lubna Mushtaq.
Afiliação
  • Shaikh K; Department of Breast Surgery, Aga Khan University Hospital.
  • Mooghal M; Department of Breast Surgery, Aga Khan University Hospital.
  • Ameen A; Department of Radiology, Aga Khan University Hospital Karachi.
  • Khan W; Department of Surgery and Medicine, Dow University of Health Sciences.
  • Zeeshan S; Department of Surgery, Aga Khan University Hospital Karachi, Pakistan.
  • Vohra LM; Department of Surgery, Aga Khan University Hospital Karachi, Pakistan.
J Pak Med Assoc ; 74(4 (Supple-4)): S43-S48, 2024 Apr.
Article em En | MEDLINE | ID: mdl-38712408
ABSTRACT
This narrative review explores the transformative potential of Artificial Intelligence (AI) and advanced imaging techniques in predicting Pathological Complete Response (pCR) in Breast Cancer (BC) patients undergoing Neo-Adjuvant Chemotherapy (NACT). Summarizing recent research findings underscores the significant strides made in the accurate assessment of pCR using AI, including deep learning and radiomics. Such AI-driven models offer promise in optimizing clinical decisions, personalizing treatment strategies, and potentially reducing the burden of unnecessary treatments, thereby improving patient outcomes. Furthermore, the review acknowledges the potential of AI to address healthcare disparities in Low- and Middle-Income Countries (LMICs), where accessible and scalable AI solutions may enhance BC management. Collaboration and international efforts are essential to fully unlock the potential of AI in BC care, offering hope for a more equitable and effective approach to treatment worldwide.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Inteligência Artificial Limite: Female / Humans Idioma: En Revista: J Pak Med Assoc Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Inteligência Artificial Limite: Female / Humans Idioma: En Revista: J Pak Med Assoc Ano de publicação: 2024 Tipo de documento: Article