Leukemia

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 goals of this study were to determine robust and reproducible optical phase signatures of cell lines for classification with machine learning and to correlate optical phase parameters to motile behavior. Digital holographic microscopy (DHM) reconstructed phase maps of cells from two pairs of cancer an...

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. The subject of a controller design approach for these models in order to find the best rate of drug injection during the course of treatment has recently attracted much attention. The rate of drug injections is very important in chemotherapy, as it not only causes cancer cells to die, but also kills...

Qualification of a chemotherapy-compounding robot.

KIRO® Oncology (Kiro Grifols, Spain) is a robotic system for automated compounding of sterile injectable drugs including intravenous cytotoxic treatme...

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 osteosarcoma. This study reports the first fully automated...

Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma.

PURPOSE: We aimed to evaluate the value of deep learning on positron emission tomography with computed tomography (PET/CT)-based radiomics for individ...

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 important issue because of the possible correlation of le...

Acute renal failure in systemic sclerosis revealing Goodpasture syndrome: "All that glitters is not scleroderma renal crisis".

The most common cause of acute renal failure in systemic sclerosis patients is scleroderma renal crisis but other etiologies have to be considered suc...

Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer's Disease.

It has demonstrated that glycogen synthase kinase 3β (GSK3β) is related to Alzheimer's disease (AD). On the basis of the world largest traditional Chi...

Quantification of apixaban in human plasma using ultra performance liquid chromatography coupled with tandem mass spectrometry.

Apixaban, an inhibitor of direct factor Xa, is used for the treatment of venous thromboembolic events or prevention of stroke. Unlike many other antic...

FactorNet: A deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data.

Due to the large numbers of transcription factors (TFs) and cell types, querying binding profiles of all valid TF/cell type pairs is not experimentall...

Combination of Peri- and Intratumoral Radiomic Features on Baseline CT Scans Predicts Response to Chemotherapy in Lung Adenocarcinoma.

PURPOSE: To identify the role of radiomics texture features both within and outside the nodule in predicting time to progression (TTP) and overall su...

Knowledge Domain and Emerging Trends on Echinococcosis Research: A Scientometric Analysis.

The echinococcosis of humans and animals is a chronic helminthic disease caused by the larva of genus tapeworms. It is a globally distributed disease...

Detection of chromosome structural variation by targeted next-generation sequencing and a deep learning application.

Molecular testing is increasingly important in cancer diagnosis. Targeted next generation sequencing (NGS) is widely accepted method but structural va...

Hybrid Rehabilitation Therapies on Upper-Limb Function and Goal Attainment in Chronic Stroke.

This study examined the treatment effects between unilateral hybrid therapy (UHT; unilateral robot-assisted therapy [RT] + modified constraint-induced...

Partially spatially coherent digital holographic microscopy and machine learning for quantitative analysis of human spermatozoa under oxidative stress condition.

Semen quality assessed by sperm count and sperm cell characteristics such as morphology and motility, is considered to be the main determinant of men'...

Relative Factors Analysis of Imatinib Trough Concentration in Chinese Patients with Gastrointestinal Stromal Tumor.

AIMS: Imatinib plasma trough levels (IM Cmin) have been reported to have a considerable clinical impact in patients with gastrointestinal stromal tumo...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, wh...

Bone Marrow Cells Detection: A Technique for the Microscopic Image Analysis.

In the detection of myeloproliferative, the number of cells in each type of bone marrow cells (BMC) is an important parameter for the evaluation. In t...

Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila.

Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to chan...

Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning.

The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analyt...