For the last few years, computer-aided diagnosis (CAD) has been increasing rapidly. Numerous machine learning algorithms have been developed to identify different diseases, e.g., leukemia. Leukemia is a white blood cells- (WBC-) related illness affec...
International journal of laboratory hematology
Sep 9, 2019
Machine learning (ML) offers opportunities to advance pathological diagnosis, especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is time-consuming and challenging in many areas globally and there is a growing tr...
Clinical lymphoma, myeloma & leukemia
Dec 20, 2015
BACKGROUND: Monitoring renal function is important in imatinib-treated patients with chronic myeloid leukemia because serum creatinine may increase during the course of therapy. The mechanism of this increase and its reversibility on treatment cessat...
Leukemia diagnosis based on bone marrow cell morphology primarily relies on the manual microscopy of bone marrow smears. However, this method is greatly affected by subjective factors and tends to lead to misdiagnosis. This study proposes using bone ...
Combinatorial chemistry & high throughput screening
Jan 1, 2020
AIM AND OBJECTIVE: Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia can be classified into four types: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML)...
Chemical communications (Cambridge, England)
Jan 10, 2019
Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation...
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