Hematology

Leukemia

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

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Combination of Estradiol with Leukemia Inhibitory Factor Stimulates Granulosa Cells Differentiation into Oocyte-Like Cells.

Previous studies have documented that cumulus granulosa cells (GCs) can trans-differentiation into ...

Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In th...

MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature.

In spite of the efforts in developing and maintaining accurate variant databases, a large number of ...

Learn from one data set to classify all - A multi-target domain adaptation approach for white blood cell classification.

BACKGROUND AND OBJECTIVE: Traditional machine learning methods assume that both training and test da...

Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study.

The last two decades saw the establishment of three-dimensional (3D) cell cultures as an acknowledge...

A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning.

Response to Neoadjuvant chemotherapy (NAC) has demonstrated a high correlation to survival in locall...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall surv...

Robot-assisted combined pancreatectomy/hepatectomy for metastatic pancreatic acinar cell carcinoma: case report and review of the literature.

Acinar cell carcinoma (ACC) of the pancreas is a rare neoplasm with less aggressive behavior than du...

Hybrid adversarial-discriminative network for leukocyte classification in leukemia.

PURPOSE: Leukemia is a lethal disease that is harmful to bone marrow and overall blood health. The c...

An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.

Relatively little is known about the molecular pathways influenced by cannabis use in humans. We us...

Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3...

Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.

PURPOSE: Neoadjuvant chemotherapy (NAC) aims to minimize the tumor size before surgery. Predicting r...

Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma.

Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic ...

Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States.

Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the Unit...

Hematologist-Level Classification of Mature B-Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data.

The wealth of information captured by multiparameter flow cytometry (MFC) can be analyzed by recent ...

Chemical Degradation of Intravenous Chemotherapy Agents and Opioids by a Novel Instrument.

To assess chemical degradation of various liquid chemotherapy and opioid drugs in the novel RxDestr...

Acute myeloid leukemia and artificial intelligence, algorithms and new scores.

Artificial intelligence, and more narrowly machine-learning, is beginning to expand humanity's capac...

Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables.

Pediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder prese...

Beyond the limitation of targeted therapy: Improve the application of targeted drugs combining genomic data with machine learning.

Precision oncology involves effectively selecting drugs for cancer patients and planning an effectiv...

Robot technology identifies a Parkinsonian therapeutics repurpose to target stem cells of glioblastoma.

Glioblastoma is a heterogeneous lethal disease, regulated by a stem-cell hierarchy and the neurotra...

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.

BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complet...

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