Leukemia

Leukemia classification using the deep learning method of CNN.

BACKGROUND: Processing Low-Intensity Medical Images (LI-MI) is difficult as outcomes are varied when...

Clinical insights into hematologic malignancies and comparative analysis of molecular signatures of acute myeloid leukemia in different ethnicities using an artificial intelligence offering.

Next generation sequencing generates copious amounts of genomics data, causing manual interpretation...

scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network.

Advances in single-cell RNA sequencing (scRNA-seq) have furthered the simultaneous classification of...

Development and Validation of a Deep Learning CT Signature to Predict Survival and Chemotherapy Benefit in Gastric Cancer: A Multicenter, Retrospective Study.

OBJECTIVE: We aimed to develop a deep learning-based signature to predict prognosis and benefit from...

Machine learning integrates genomic signatures for subclassification beyond primary and secondary acute myeloid leukemia.

Although genomic alterations drive the pathogenesis of acute myeloid leukemia (AML), traditional cla...

Machine learning finds new AML subtypes.

AniAMPpred: artificial intelligence guided discovery of novel antimicrobial peptides in animal kingdom.

With advancements in genomics, there has been substantial reduction in the cost and time of genome s...

Data Enhancement and Deep Learning for Bone Age Assessment using The Standards of Skeletal Maturity of Hand and Wrist for Chinese.

Conventional methods for artificial age determination of skeletal bones have several problems, such ...

RoBoT: a robust Bayesian hypothesis testing method for basket trials.

A basket trial in oncology encompasses multiple "baskets" that simultaneously assess one treatment i...

[A novel attention fusion network-based multiple instance learning framework to automate diagnosis of chronic gastritis with multiple indicators].

To explore the performance of the attention-multiple instance learning (MIL) framework, an attentio...

Pan-Tissue Aging Clock Genes That Have Intimate Connections with the Immune System and Age-Related Disease.

In our recent transcriptomic meta-analysis, we used random forest machine learning to accurately pre...

Applying Machine Learning to Stem Cell Culture and Differentiation.

Machine learning techniques are increasingly becoming incorporated into biological research workflow...

Prediction of Neutropenic Events in Chemotherapy Patients: A Machine Learning Approach.

PURPOSE: Severe and febrile neutropenia present serious hazards to patients with cancer undergoing c...

Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework.

Origins of replication sites (ORIs), which refers to the initiative locations of genomic DNA replica...

A Deep Learning System for Synthetic Knee Magnetic Resonance Imaging: Is Artificial Intelligence-Based Fat-Suppressed Imaging Feasible?

MATERIALS AND METHODS: This single-center study was approved by the institutional review board. Arti...

scCancer: a package for automated processing of single-cell RNA-seq data in cancer.

Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis ...

CODEX, a neural network approach to explore signaling dynamics landscapes.

Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield...

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

The case is a 68‒year‒old male, who had been diagnosed with acute myeloid leukemia(AML)prior to rect...

[Banded chromosome images recognition based on dense convolutional network with segmental recalibration].

Human chromosomes karyotyping is an important means to diagnose genetic diseases. Chromosome image t...

Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space.

It is well known that the development of drug resistance in cancer cells can lead to changes in cell...

Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets.

BACKGROUND: The accuracy of current prediction tools for ischaemic and bleeding events after an acut...