%0 Journal Article
%T From microscope to micropixels: A rapid review of artificial intelligence for the peripheral blood film.
%A Fan BE
%A Yong BSJ
%A Li R
%A Wang SSY
%A Aw MYN
%A Chia MF
%A Chen DTY
%A Neo YS
%A Occhipinti B
%A Ling RR
%A Ramanathan K
%A Ong YX
%A Lim KGE
%A Wong WYK
%A Lim SP
%A Latiff STBA
%A Shanmugam H
%A Wong MS
%A Ponnudurai K
%A Winkler S
%J Blood Rev
%V 64
%N 0
%D 2024 Mar 19
%M 38016837
%F 10.626
%R 10.1016/j.blre.2023.101144
%X Artificial intelligence (AI) and its application in classification of blood cells in the peripheral blood film is an evolving field in haematology. We performed a rapid review of the literature on AI and peripheral blood films, evaluating the condition studied, image datasets, machine learning models, training set size, testing set size and accuracy. A total of 283 studies were identified, encompassing 6 broad domains: malaria (n = 95), leukemia (n = 81), leukocytes (n = 72), mixed (n = 25), erythrocytes (n = 15) or Myelodysplastic syndrome (MDS) (n = 1). These publications have demonstrated high self-reported mean accuracy rates across various studies (95.5% for malaria, 96.0% for leukemia, 94.4% for leukocytes, 95.2% for mixed studies and 91.2% for erythrocytes), with an overall mean accuracy of 95.1%. Despite the high accuracy, the challenges toward real world translational usage of these AI trained models include the need for well-validated multicentre data, data standardisation, and studies on less common cell types and non-malarial blood-borne parasites.