TY - JOUR
T1 - Artificial intelligence in sickle disease
AU - Elsabagh, Ahmed Adel
AU - Elhadary, Mohamed
AU - Elsayed, Basel
AU - Elshoeibi, Amgad Mohamed
AU - Ferih, Khaled
AU - Kaddoura, Rasha
AU - Alkindi, Salam
AU - Alshurafa, Awni
AU - Alrasheed, Mona
AU - Alzayed, Abdullah
AU - Al-Abdulmalek, Abdulrahman
AU - Altooq, Jaffer Abduljabber
AU - Yassin, Mohamed
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, including sickle cell disease (SCD). AI has started new ways to improve risk stratification and diagnosing SCD complications early, allowing rapid intervention and reallocation of resources to high-risk patients. We reviewed the literature for established and new AI applications that may enhance management of SCD through advancements in diagnosing SCD and its complications, risk stratification, and the effect of AI in establishing an individualized approach in managing SCD patients in the future. Aim: to review the benefits and drawbacks of resources utilizing AI in clinical practice for improving the management for SCD cases.
AB - Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, including sickle cell disease (SCD). AI has started new ways to improve risk stratification and diagnosing SCD complications early, allowing rapid intervention and reallocation of resources to high-risk patients. We reviewed the literature for established and new AI applications that may enhance management of SCD through advancements in diagnosing SCD and its complications, risk stratification, and the effect of AI in establishing an individualized approach in managing SCD patients in the future. Aim: to review the benefits and drawbacks of resources utilizing AI in clinical practice for improving the management for SCD cases.
KW - Artificial intelligence
KW - Convolutional neural networks
KW - Hemoglobinopathies
KW - Machine learning
KW - Sickle cell
UR - http://www.scopus.com/inward/record.url?scp=85162910621&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85162910621&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/fbb6fe0c-1ce7-3b12-92a0-cf92c34ab067/
U2 - 10.1016/j.blre.2023.101102
DO - 10.1016/j.blre.2023.101102
M3 - Article
C2 - 37355428
AN - SCOPUS:85162910621
SN - 0268-960X
VL - 61
SP - 101102
JO - Blood Reviews
JF - Blood Reviews
M1 - 101102
ER -