Hematology

Leukemia

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

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Acute stroke rehabilitation for gait training with cyborg type robot Hybrid Assistive Limb: A pilot study.

Robot-assisted gait training following acute stroke could allow patients with severe disability to r...

Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning.

Minimal residual disease (MRD) as measured by multiparameter flow cytometry (FCM) is an independent ...

A practical guide to intelligent image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs ...

Neural networks versus Logistic regression for 30 days all-cause readmission prediction.

Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within...

Machine Learning Models Combined with Virtual Screening and Molecular Docking to Predict Human Topoisomerase I Inhibitors.

In this work, random forest (RF), support vector machine, k-nearest neighbor and C4.5 decision tree,...

Convolutional Neural Networks for Recognition of Lymphoblast Cell Images.

This paper presents the recognition for WHO classification of acute lymphoblastic leukaemia (ALL) su...

GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation.

Cell segmentation in microscopy images is a common and challenging task. In recent years, deep neura...

Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.

Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature...

Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

The question of whether ultrasound point shear wave elastography can differentiate renal cell carcin...

Enhancing Acute Oral Toxicity Predictions by using Consensus Modeling and Algebraic Form-Based 0D-to-2D Molecular Encodes.

Quantitative structure-activity relationships (QSAR) are introduced to predict acute oral toxicity (...

Screening and Diagnosis of Chronic Pharyngitis Based on Deep Learning.

Chronic pharyngitis is a common disease, which has a long duration and a wide range of onset. It is ...

All-optical spiking neurosynaptic networks with self-learning capabilities.

Software implementations of brain-inspired computing underlie many important computational tasks, fr...

Machine-learned target volume delineation of F-FDG PET images after one cycle of induction chemotherapy.

Biological tumour volume (GTV) delineation on F-FDG PET acquired during induction chemotherapy (ICT)...

Neural network and support vector machine for the prediction of chronic kidney disease: A comparative study.

This paper aims to assist in the prevention of Chronic Kidney Disease (CKD) by utilizing machine lea...

Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Robust and reproducible profiling of cell lines is essential for phenotypic screening assays. The go...

Derivation of an optimal trajectory and nonlinear adaptive controller design for drug delivery in cancerous tumor chemotherapy.

Numerous models have investigated cancer behavior by considering different factors in chemotherapy. ...

Qualification of a chemotherapy-compounding robot.

KIRO® Oncology (Kiro Grifols, Spain) is a robotic system for automated compounding of sterile inject...

Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.

Pathological estimation of tumor necrosis after chemotherapy is essential for patients with osteosar...

Use of Machine Learning in the Analysis of Indoor ELF MF Exposure in Children.

Characterization of children exposure to extremely low frequency (ELF) magnetic fields is an importa...

ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels.

BACKGROUND: Although software tools abound for the comparison, analysis, identification, and classif...

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