TY - JOUR
T1 - Transforming breast cancer care
T2 - harnessing the power of artificial intelligence and imaging for predicting pathological complete response. a narrative review
AU - Shaikh, Kulsoom
AU - Mooghal, Mehwish
AU - Ameen, Abdullah
AU - Khan, Wajiha
AU - Zeeshan, Sana
AU - Vohra, Lubna Mushtaq
N1 - Publisher Copyright:
© 2024 Pakistan Medical Association. All rights reserved.
PY - 2024/4
Y1 - 2024/4
N2 - 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.
AB - 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.
KW - Artificial Intelligence
KW - Breast Neoplasms
KW - Healthcare Disparities
KW - Learning
KW - Magnetic Resonance Imaging
KW - Neoadjuvant Therapy
KW - Neoadjuvant Therapy
KW - Pathological Response
KW - Radiomics
UR - http://www.scopus.com/inward/record.url?scp=85192633424&partnerID=8YFLogxK
U2 - 10.47391/JPMA.AKU-9S-07
DO - 10.47391/JPMA.AKU-9S-07
M3 - Article
C2 - 38712408
AN - SCOPUS:85192633424
SN - 0030-9982
VL - 74
SP - S43-S48
JO - Journal of the Pakistan Medical Association
JF - Journal of the Pakistan Medical Association
IS - 4
ER -