Leukemia

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds.

Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for impor...

Robot controlled, continuous passive movement of the ankle reduces spinal cord excitability in participants with spasticity: a pilot study.

Spasticity of the ankle reduces quality of life by impeding walking and other activities of daily li...

Choosing Clinical Variables for Risk Stratification Post-Acute Coronary Syndrome.

Most risk stratification methods use expert opinion to identify a fixed number of clinical variables...

[Prediction of chemotherapy response in primary osteosarcoma using the machine learning technique on radiomic data].

INTRODUCTION: Osteosarcoma is the most common malignant bone tumor before 25 years of age. Response ...

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevan...

A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1.

Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells.

Bone marrow aspirate (BMA) differential cell counts (DCCs) are critical for the classification of he...

All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration ICs for 8558 Novartis Assays.

Profile-quantitative structure-activity relationship (pQSAR) is a massively multitask, two-step mach...

Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning.

Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which ...

Machine learning applications in the diagnosis of leukemia: Current trends and future directions.

Machine learning (ML) offers opportunities to advance pathological diagnosis, especially with increa...

Designing combination therapies with modeling chaperoned machine learning.

Chemotherapy resistance is a major challenge to the effective treatment of cancer. Thus, a systemati...

Automated Counting of Cancer Cells by Ensembling Deep Features.

High-content and high-throughput digital microscopes have generated large image sets in biological e...

Multioutput Perturbation-Theory Machine Learning (PTML) Model of ChEMBL Data for Antiretroviral Compounds.

Retroviral infections, such as HIV, are, until now, diseases with no cure. Medicine and pharmaceutic...

Artificial Intelligence in Nephrology: Core Concepts, Clinical Applications, and Perspectives.

Artificial intelligence is playing an increasingly important role in many fields of medicine, assist...

Comparing regression, naive Bayes, and random forest methods in the prediction of individual survival to second lactation in Holstein cattle.

In this study, we compared multiple logistic regression, a linear method, to naive Bayes and random ...

Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning.

Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of exp...

mDixon-Based Synthetic CT Generation for PET Attenuation Correction on Abdomen and Pelvis Jointly Using Transfer Fuzzy Clustering and Active Learning-Based Classification.

We propose a new method for generating synthetic CT images from modified Dixon (mDixon) MR data. The...

Prediction of Chemotherapy Response of Osteosarcoma Using Baseline F-FDG Textural Features Machine Learning Approaches with PCA.

PURPOSE: Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical i...

Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's larges...

Patient-based prediction algorithm of relapse after allo-HSCT for acute Leukemia and its usefulness in the decision-making process using a machine learning approach.

Although allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for hi...

Characterization and potential antitumor effect of a heteropolysaccharide produced by the red alga .

Taking into account the rising trend of the incidence of cancers of various organs, effective therap...