AI Medical Compendium Topic

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Leukemia, Myeloid, Acute

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[A Case of Descending Colon and Rectal Cancer with Acute Myeloid Leukemia Performed Robot‒Assisted Hartmann's Procedure].

Gan to kagaku ryoho. Cancer & chemotherapy
The case is a 68‒year‒old male, who had been diagnosed with acute myeloid leukemia(AML)prior to rectal cancer surgery, was referred to our hospital for treatment in July 2019. We planned to treat the AML first, and then the colorectal cancer. After c...

AML, ALL, and CML classification and diagnosis based on bone marrow cell morphology combined with convolutional neural network: A STARD compliant diagnosis research.

Medicine
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 ...

Deep Learning for Acute Myeloid Leukemia Diagnosis.

Journal of medicine and life
By changing the lifestyle and increasing the cancer incidence, accurate diagnosis becomes a significant medical action. Today, DNA microarray is widely used in cancer diagnosis and screening since it is able to measure gene expression levels. Analyzi...

Analysis of Four Types of Leukemia Using Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Scores.

Combinatorial chemistry & high throughput screening
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)...

A BLSTM with Attention Network for Predicting Acute Myeloid Leukemia Patient's Prognosis using Comprehensive Clinical Parameters.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The prognosis management is crucial for highrisk disease like Acute Myeloid Leukemia (AML) in order to support decisions of clinical treatment. However, the challenges of accurate and consistent forecasting lie in the high variability of the disease ...

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study.

Blood advances
Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytogenetic abnormalities and gene mutations are important predictors of outcome, 50% to 70% of AMLs harb...

Proteomics Analysis of FLT3-ITD Mutation in Acute Myeloid Leukemia Using Deep Learning Neural Network.

Annals of clinical and laboratory science
Deep Learning can significantly benefit cancer proteomics and genomics. In this study, we attempted to determine a set of critical proteins that were associated with the FLT3-ITD mutation in newly-diagnosed acute myeloid leukemia patients. A Deep Lea...

Automated analysis of acute myeloid leukemia minimal residual disease using a support vector machine.

Oncotarget
We investigated the ability of support vector machines (SVM) to analyze minimal residual disease (MRD) in flow cytometry data from patients with acute myeloid leukemia (AML) automatically, objectively and standardly. The initial disease data and MRD ...