AIMC Topic: Hematologic Neoplasms
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An AI-Aided Diagnostic Framework for Hematologic Neoplasms Based on Morphologic Features and Medical Expertise.
Laboratory investigation; a journal of technical methods and pathology
Jan 10, 2023
A morphologic examination is essential for the diagnosis of hematological diseases. However, its conventional manual operation is time-consuming and laborious. Herein, we attempt to establish an artificial intelligence (AI)-aided diagnostic framework...
Therapy resistance mechanisms in hematological malignancies.
International journal of cancer
Aug 23, 2022
Hematologic malignancies are model diseases for understanding neoplastic transformation and serve as prototypes for developing effective therapies. Indeed, the concept of systemic cancer therapy originated in hematologic malignancies and has guided t...
Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 21, 2022
Advancing diagnostic testing capabilities such as clinical next generation sequencing methods offer the potential to diagnose, risk stratify, and guide specialized treatment, but must be balanced against the escalating costs of healthcare to identify...
Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model.
Scientific reports
Jan 19, 2022
Blood cancer has been a growing concern during the last decade and requires early diagnosis to start proper treatment. The diagnosis process is costly and time-consuming involving medical experts and several tests. Thus, an automatic diagnosis system...
Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.
International journal of hematology
Jun 25, 2021
This study aimed to establish a predictive model to identify children with hematologic malignancy at high risk for delayed clearance of high-dose methotrexate (HD-MTX) based on machine learning. A total of 205 patients were recruited. Five variables ...
Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence.
Acta cytologica
Jul 28, 2020
INTRODUCTION: The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological malignancy. Manual bone marrow differential count is time consuming and lacks consistency. In this study, a...
Stable gene selection by self-representation method in fuzzy sample classification.
Medical & biological engineering & computing
Mar 24, 2020
In recent years, microarray technology and gene expression profiles have been widely used to detect, predict, or classify the samples of various diseases. The presence of large genes in these profiles and the small number of samples are known challen...
Artificial Intelligence based Models for Screening of Hematologic Malignancies using Cell Population Data.
Scientific reports
Mar 16, 2020
Cell Population Data (CPD) provides various blood cell parameters that can be used for differential diagnosis. Data analytics using Machine Learning (ML) have been playing a pivotal role in revolutionizing medical diagnostics. This research presents ...
Qualitative, Exploratory, and Multidimensional Study of Telepresence Robots for Overcoming Social Isolation of Children and Adolescents Hospitalized in Onco-Hematology.
Journal of adolescent and young adult oncology
Oct 30, 2019
Treatment of pediatric cancers and hematological malignancies requires long periods of isolation in a sterile room. To promote family connections, telepresence robots have been made available in the homes of hospitalized patients. Our aim was to eva...
[Development and national rollout of electronic decision support systems using artificial intelligence in the field of onco-hematology].
Magyar onkologia
Oct 30, 2019
Systematic, structured and longitudinal collection of realtime Big Patient Data and the analysis of aggregated diagnostic, therapeutic and therapy response data of onco-hematologic patients leads to the development of nationwide dynamic disease regis...
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