Next Article in Journal
Anticholinergic Burden in Individuals with Down Syndrome: An Examination of Risk and Clinical Implications
Previous Article in Journal
From Anatomical Staging to Precision Prognostication: Evolution of Gallbladder Cancer Staging Across AJCC Editions and the 2025 UICC TNM Update
Previous Article in Special Issue
Clinical Application of Artificial Intelligence in Anesthesiology: A Multicenter Retrospective Comparison Between Human Anesthetic Decisions and Algorithmic Recommendations in Non-Cardiac Surgery
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JPM
Volume 16
Issue 8
10.3390/jpm16080397
jpm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia

by
Pasquale Niscola
1,*,
Valentina Gianfelici
1,
Roberta Laureana
1,
Marco Giovannini
1,
Carla Mazzone
1,
Fabio Efficace
2 and
Maria Ilaria Del Principe
1,3
1
Hematology Unit, Medical Area Department, S. Eugenio Hospital (ASL Roma 2), Piazzale dell’Umanesimo 10, 00144 Rome, Italy
2
Italian Group for Adult Hematologic Diseases (GIMEMA), Data Center and Health Outcomes Research Unit, 00168 Rome, Italy
3
Hematology Unit, Department of Biomedicine and Prevention, University Tor Vergata of Rome, 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2026, 16(8), 397; https://doi.org/10.3390/jpm16080397
Submission received: 31 May 2026 / Revised: 15 July 2026 / Accepted: 23 July 2026 / Published: 24 July 2026
(This article belongs to the Special Issue Artificial Intelligence for Personalized Medicine: Bridging Innovative Technologies and Patient-Centric Care)
Browse Figure
Versions Notes

Abstract

Acute Myeloid Leukemia (AML) is a heterogeneous group of aggressive blood-related cancers that arise from the hematopoietic system, requiring specific treatments due to their genetic diversity and complexity. Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with considerable potential to help manage AML. The application of AI approaches, such as Machine Learning (ML) models and Deep Learning (DL) algorithms, has been shown to aid risk stratification, diagnosis, treatment planning, and surveillance. This review highlights recent developments in AI applications for the personalized management of AML. We focus specifically on three major axes of personalization in AML: (1) the use of predictive models combining different data sources to improve prognostic assessment and guide risk-adaptive treatments; (2) prediction of treatment responses to various therapies based on data analysis; and (3) the use of AI for monitoring and adaptive trials in AML patients.
Keywords: acute myeloid leukemia; artificial intelligence; convolutional neural networks; deep learning algorithms; diagnosis; fitness; genomic alterations; leukemia classification; machine learning; molecular testing; measurable residual disease; patient-reported outcomes; personalized medicine; prognostic value; quality of life; targeted therapies acute myeloid leukemia; artificial intelligence; convolutional neural networks; deep learning algorithms; diagnosis; fitness; genomic alterations; leukemia classification; machine learning; molecular testing; measurable residual disease; patient-reported outcomes; personalized medicine; prognostic value; quality of life; targeted therapies
Graphical Abstract

Share and Cite

MDPI and ACS Style

Niscola, P.; Gianfelici, V.; Laureana, R.; Giovannini, M.; Mazzone, C.; Efficace, F.; Principe, M.I.D. Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia. J. Pers. Med. 2026, 16, 397. https://doi.org/10.3390/jpm16080397

AMA Style

Niscola P, Gianfelici V, Laureana R, Giovannini M, Mazzone C, Efficace F, Principe MID. Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia. Journal of Personalized Medicine. 2026; 16(8):397. https://doi.org/10.3390/jpm16080397

Chicago/Turabian Style

Niscola, Pasquale, Valentina Gianfelici, Roberta Laureana, Marco Giovannini, Carla Mazzone, Fabio Efficace, and Maria Ilaria Del Principe. 2026. "Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia" Journal of Personalized Medicine 16, no. 8: 397. https://doi.org/10.3390/jpm16080397

APA Style

Niscola, P., Gianfelici, V., Laureana, R., Giovannini, M., Mazzone, C., Efficace, F., & Principe, M. I. D. (2026). Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia. Journal of Personalized Medicine, 16(8), 397. https://doi.org/10.3390/jpm16080397

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop