Hematology

Leukemia

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

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CKLF and IL1B transcript levels at diagnosis are predictive of relapse in children with pre-B-cell acute lymphoblastic leukaemia.

Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic ...

Infrared Metasurface Augmented by Deep Learning for Monitoring Dynamics between All Major Classes of Biomolecules.

Insights into the fascinating molecular world of biological processes are crucial for understanding ...

Biomimetic FPGA-based spatial navigation model with grid cells and place cells.

The mammalian spatial navigation system is characterized by an initial divergence of internal repres...

Robotic chemotherapy compounding: A multicenter productivity approach.

INTRODUCTION: The aim of this study is to compare productivity of the KIRO Oncology compounding robo...

Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality.

Machine learning promises to assist physicians with predictions of mortality and of other future cli...

TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties.

Immunotherapy is a research area with great potential in drug discovery for cancer treatment. Becaus...

BloodCaps: A capsule network based model for the multiclassification of human peripheral blood cells.

BACKGROUND AND OBJECTIVE: The classification of human peripheral blood cells yields significance in ...

Imaging-Based Outcome Prediction of Acute Intracerebral Hemorrhage.

We hypothesized that imaging-only-based machine learning algorithms can analyze non-enhanced CT scan...

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level.

Rapid detection of food-borne pathogens in early food contamination is a permanent topic to ensure f...

Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition.

In this work, we aim to address the problem of human interaction recognition in videos by exploring ...

Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and ra...

Identification of drug combinations on the basis of machine learning to maximize anti-aging effects.

Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging ...

Radiomics to better characterize small renal masses.

PURPOSE: Radiomics is a specific field of medical research that uses programmable recognition tools ...

A Reliable Machine Learning Approach applied to Single-Cell Classification in Acute Myeloid Leukemia.

Machine Learning research applied to the medical field is increasing. However, few of the proposed a...

Artificial immune system features added to breast cancer clinical data for machine learning (ML) applications.

We here propose a new method of combining a mathematical model that describes a chemotherapy treatme...

Improving Global Healthcare and Reducing Costs Using Second-Generation Artificial Intelligence-Based Digital Pills: A Market Disruptor.

Improving global health requires making current and future drugs more effective and affordable. Whi...

Dynamics of Systemic Inflammation as a Function of Developmental Stage in Pediatric Acute Liver Failure.

The Pediatric Acute Liver Failure (PALF) study is a multicenter, observational cohort study of infan...

Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.

The analysis of single-cell genomics data presents several statistical challenges, and extensive eff...

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