Open Research Papers

In this database you will find an archive of leukemia, other blood/bone marrow cancer & COVID-19 related research papers.

In this database you will find an archive of leukemia, other blood/bone marrow cancer & COVID-19 related research papers.

If you have information you would like to share in this database, please feel free to email us via our contact page with details.



Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics

Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics

Our results support the notion that transcriptomics combined with machine learning could be used as part of an integrated -omics approach wherein risk prediction, differential diagnosis, and subclassification of AML are achieved by genomics while diagnosis could be assisted by transcriptomic-based machine learning. AUTHORS: Stefanie Warnat-Herresthal Konstantinos Perrakis, Bernd Taschler, Matthias Becker, Kevin Baßler, Marc Beyer, Patrick Gu¨ nther,1 Jonas Schulte-Schrepping, Lea Seep, Kathrin Klee, Thomas Ulas, Torsten Haferlach, Sach Mukherjee, and Joachim L. Schultze

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Human-level recognition of blast cells in acute myeloid leukemia with convolutional neural networks

Human-level recognition of blast cells in acute myeloid leukemia with convolutional neural networks

We compile an annotated image dataset of over 18,000 white blood cells, use it to train a convolutional neural network for leukocyte classification, and evaluate the network’s performance. The network classifies the most important cell types with high accuracy. It also allows us to decide two clinically relevant questions with human-level performance, namely (i) if a given cell has blast character, and (ii) if it belongs to the cell types normally present in non-pathological blood smears. AUTHORS: Christian Matek, Simone Schwarz, Karsten Spiekermann, Carsten Marr

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Towards explainable deep neural networks (xDNN)

Towards explainable deep neural networks (xDNN)

In this paper, we propose an elegant solution that is directly addressing the bottlenecks of the traditional deep learning approaches and offers an explainable internal architecture that can outperform the existing methods, requires very little computational resources (no need for GPUs) and short training times (in the order of seconds). Authors: Plamen Angelov, Eduardo Soares

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SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification

SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification

In this paper, we build a public available SARS-CoV-2 CT scan dataset, containing 1252 CT scans that are positive for SARS-CoV-2 infection (COVID-19) and 1230 CT scans for patients non-infected by SARS-CoV-2, 2482 CT scans in total. These data have been collected from real patients in hospitals from Sao Paulo, Brazil. Authors: Plamen Angelov, Eduardo Soares

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Peripheral blood smear image analysis: A comprehensive review

Peripheral blood smear image analysis: A comprehensive review

Peripheral blood smear image examination is a part of the routine work of every laboratory. The manual examination of these images is tedious, time?consuming and suffers from interobserver variation.

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Leukemia Blood Cell Image Classification Using Convolutional Neural Network

Leukemia Blood Cell Image Classification Using Convolutional Neural Network

Acute myeloid leukemia is a type of malignant blood cell cancer that can affect both children and adults. There are 60,140 people were expected to be diagnosed with Leukemia in 2016, according to the Leukemia and Lymphoma Society. In order to get the most effective treatment, the patient needs early diagnosis. AUTHORS: Thanh, T T P, Vununu, Caleb, Atoev, Sukhrob, Lee, Suk-Hwan, Kwon, Ki-Ryong.

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Image processing and machine learning in the morphological analysis of blood cells

Image processing and machine learning in the morphological analysis of blood cells

This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears.

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Diagnosing Leukemia in Blood Smear Images Using an Ensemble of Classifiers and Pre-Trained Convolutional Neural Networks

Diagnosing Leukemia in Blood Smear Images Using an Ensemble of Classifiers and Pre-Trained Convolutional Neural Networks

Leukemia is a worldwide disease. In this paper we demonstrate that it is possible to build an automated, efficient and rapid leukemia diagnosis system.

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Detection of leukemia and its types using image processing and machine learning

Detection of leukemia and its types using image processing and machine learning

This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears.

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Classification of acute myelogenous leukemia in blood microscopic images using supervised classifier

Classification of acute myelogenous leukemia in blood microscopic images using supervised classifier

Blood cancer is a form of cancer which attacks the blood, bone marrow, or lymphatic system. It is diagnosed with a blood test in which specific types of blood cells are counted by hematologist. We considered only acute myelogenous leukemia, which is one of the blood cancer type which categories under acute leukemia and it mostly comes among adults. AUTHORS: Goutam, D., Sailaja, S.

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Acute Leukemia Classification Using Convolution Neural Network in Clinical Decision Support System

Acute Leukemia Classification Using Convolution Neural Network in Clinical Decision Support System

Leukemia induced death has been listed in the top ten most dangerous mortality basis for human being.

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All-IDB: The acute lymphoblastic leukemia image database for image processing

All-IDB: The acute lymphoblastic leukemia image database for image processing

The visual analysis of peripheral blood samples is an important test in the procedures for the diagnosis of leukemia.

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