Leukemia

Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction.

Banks and financial institutions are vulnerable to money laundering (ML) as a result of crime proceeds infiltrating banks in the form of significant cash deposits. Improved financial crime compliance processes and systems enable anti-ML (AML) analysts to devote considerable time and effort to case investigation and process quality work, thereby lowering financial risks by reporting suspicious act...

[Heart failure care in a digitalized future : A discourse on resource-sparing structures and self-determined patients].

Digital health solutions, applications of artificial intelligence (AI) and new technologies, such as cardiac magnetic resonance imaging and cardiac human genetics are currently being validated in cardiac healthcare pathways. They show promising approaches for improving existing healthcare structures in the future by strengthening the focus on predictive, preventive and personalized medicine. In ad...

Automated detection of leukemia by pretrained deep neural networks and transfer learning: A comparison.

Leukemia is usually diagnosed by viewing the smears of blood and bone marrow using microscopes and complex Cytochemical tests can be used to authorize...

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.

Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery...

Prediction of Essential Genes in Comparison States Using Machine Learning.

Identifying essential genes in comparison states (EGS) is vital to understanding cell differentiation, performing drug discovery, and identifying dise...

Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art.

Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technologies in many day-to-day applications. Translation...

Prediction for the Risk of Multiple Chronic Conditions Among Working Population in the United States With Machine Learning Models.

Chronic diseases have become the most prevalent and costly health conditions in the healthcare industry, deteriorating the quality of life, adversely...

SCMAG: A Semisupervised Single-Cell Clustering Method Based on Matrix Aggregation Graph Convolutional Neural Network.

Clustering analysis is one of the most important technologies for single-cell data mining. It is widely used in the division of different gene sequenc...

5FU-loaded PCL/Chitosan/FeO Core-Shell Nanofibers Structure: An Approach to Multi-Mode Anticancer System.

5-Fluorouracil (5FU) and FeO nanoparticles were encapsulated in core-shell polycaprolactone (PCL)/chitosan (CS) nanofibers as a multi-mode anticancer...

Study on the identification of resistance of rice blast based on near infrared spectroscopy.

Rice Blast is the most devastating rice disease which poses a serious threat to the safe production of rice. The most effective way to prevent rice bl...

Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.

High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-...

Multimodal deep learning models for the prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

The achievement of the pathologic complete response (pCR) has been considered a metric for the success of neoadjuvant chemotherapy (NAC) and a powerfu...

Robot-Assisted Laparoscopic Management of Bladder/Prostate Rhabdomyosarcoma in Children: Initial Series and 1-Year Outcomes.

To present our preliminary experiences of robot-assisted laparoscopic radical or partial cystectomy for bladder/prostate rhabdomyosarcoma (B/P RMS) i...

Deep Learning-Based CT Imaging in Diagnosing Myeloma and Its Prognosis Evaluation.

Imaging examination plays an important role in the early diagnosis of myeloma. The study focused on the segmentation effects of deep learning-based mo...

Deep learning detects acute myeloid leukemia and predicts NPM1 mutation status from bone marrow smears.

The evaluation of bone marrow morphology by experienced hematopathologists is essential in the diagnosis of acute myeloid leukemia (AML); however, it ...

Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs.

Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop...

Ensemble based machine learning approach for prediction of glioma and multi-grade classification.

Glioma is the most pernicious cancer of the nervous system, with histological grade influencing the survival of patients. Despite many studies on the ...

Automated segmentation of biventricular contours in tissue phase mapping using deep learning.

Tissue phase mapping (TPM) is an MRI technique for quantification of regional biventricular myocardial velocities. Despite its potential, clinical use...

Chemotherapeutic potential of Cayratia trifolia L nhexane extract on A2780 cells.

It is of interest to report the chemotherapeutic (drug target based) potential of n-hexane Cayratia trifolia L. (C.trifolia) extract on A2780 cell lin...

Using machine learning and big data to explore the drug resistance landscape in HIV.

Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to rev...