Hematology

Leukemia

Latest AI and machine learning research in leukemia for healthcare professionals.

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Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network.

In this paper, we demonstrate the feasibility and performance of deep residual neural networks for v...

Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural Networks.

BACKGROUND The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardi...

Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments.

We describe a novel method to achieve a universal, massive, and fully automated analysis of cell mot...

Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.

The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET,...

Machine Learning and Prediction of All-Cause Mortality in COPD.

BACKGROUND: COPD is a leading cause of mortality.

Predicting severe clinical events by learning about life-saving actions and outcomes using distant supervision.

Medical error is a leading cause of patient death in the United States. Among the different types of...

Classifying changes in LN-18 glial cell morphology: a supervised machine learning approach to analyzing cell microscopy data via FIJI and WEKA.

In cell-based research, the process of visually monitoring cells generates large image datasets that...

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the applic...

Correlation Between the Trajectory of the Center of Pressure and Thermography of Cancer Patients Undergoing Chemotherapy.

OBJECTIVE: The purpose of this study was to correlate potential the stabilometric parameters of baro...

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches.

Flow cytometry nowadays is among the main working instruments in modern biology paving the way for c...

Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome.

Unsupervised machine learning that can discover novel knowledge from big sequence data without prior...

Soft Clustering for Enhancing the Diagnosis of Chronic Diseases over Machine Learning Algorithms.

Chronic diseases represent a serious threat to public health across the world. It is estimated at ab...

One model to rule them all? Using machine learning algorithms to determine the number of factors in exploratory factor analysis.

Determining the number of factors is one of the most crucial decisions a researcher has to face when...

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and f...

Label-Free Leukemia Monitoring by Computer Vision.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of ...

A novel artificial intelligence protocol for finding potential inhibitors of acute myeloid leukemia.

There is currently no effective treatment for acute myeloid leukemia, and surgery is also ineffectiv...

Machine Learning Algorithms for Predicting the Recurrence of Stage IV Colorectal Cancer After Tumor Resection.

The aim of this study is to explore the feasibility of using machine learning (ML) technology to pre...

Efficient Classification of White Blood Cell Leukemia with Improved Swarm Optimization of Deep Features.

White Blood Cell (WBC) Leukaemia is caused by excessive production of leukocytes in the bone marrow,...

SDCT-AuxNet: DCT augmented stain deconvolutional CNN with auxiliary classifier for cancer diagnosis.

Acute lymphoblastic leukemia (ALL) is a pervasive pediatric white blood cell cancer across the globe...

Single-cell dispensing and 'real-time' cell classification using convolutional neural networks for higher efficiency in single-cell cloning.

Single-cell dispensing for automated cell isolation of individual cells has gained increased attenti...

Diagnosis and classification of cancer using hybrid model based on ReliefF and convolutional neural network.

Machine learning and deep learning methods aims to discover patterns out of datasets such as, microa...

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