Leukemia

Intelligence computational analysis of letrozole solubility in supercritical solvent via machine learning models.

Supercritical fluids (SCFs) can be used to prepare drugs nanoparticles with improved solubility. SCF...

Intratumoral and Peritumoral Radiomics for Predicting the Prognosis of High-grade Serous Ovarian Cancer Patients Receiving Platinum-Based Chemotherapy.

RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL) prognostic model to evalu...

Adaptive Machine Learning in Medicine: Not Human Subjects Research, Not Research at All.

Machine learning-based evaluation of prognostic factors for mortality and relapse in patients with acute lymphoblastic leukemia: a comparative simulation study.

BACKGROUND: Predicting mortality and relapse in children with acute lymphoblastic leukemia (ALL) is ...

Integrated machine learning algorithms identify KIF15 as a potential prognostic biomarker and correlated with stemness in triple-negative breast cancer.

Cancer stem cells (CSCs) have the potential to self-renew and induce cancer, which may contribute to...

Renal Cell Carcinoma Discrimination through Attenuated Total Reflection Fourier Transform Infrared Spectroscopy of Dried Human Urine and Machine Learning Techniques.

Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading...

MYC Rearrangement Prediction From LYSA Whole Slide Images in Large B-Cell Lymphoma: A Multicentric Validation of Self-supervised Deep Learning Models.

Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYC gene rearrangement ...

Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer.

We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiom...

Magnetic Torque-Driven All-Terrain Microrobots.

All-terrain microrobots possess significant potential in modern medical applications due to their su...

DeepPhoPred: Accurate Deep Learning Model to Predict Microbial Phosphorylation.

Phosphorylation is a substantial posttranslational modification of proteins that refers to adding a ...

Imatinib adherence prediction using machine learning approach in patients with gastrointestinal stromal tumor.

BACKGROUND: Nonadherence to imatinib is common in patients with gastrointestinal stromal tumor (GIST...

Association of N-terminal pro-B natriuretic peptide with all-cause mortality and cardiovascular mortality in obese and non-obese populations and the development of a machine learning prediction model: National Health and Nutrition Examination Survey (NHANES) 1999-2004.

AIMS: To explore the potential of N-terminal pro-B natriuretic peptide (NTproBNP) in identifying adv...

An open dataset for oracle bone character recognition and decipherment.

Oracle bone script, one of the earliest known forms of ancient Chinese writing, presents invaluable ...

Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristic...

An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.

RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before tre...

CNVDeep: deep association of copy number variants with neurocognitive disorders.

BACKGROUND: Copy number variants (CNVs) have become increasingly instrumental in understanding the e...

Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Recently, various modern experimental screening pipelines and assays have been developed to find pro...

MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network.

Synthetic lethality (SL) and synthetic viability (SV) are commonly studied genetic interactions in t...

Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy.

RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of the deep learning radiomics ...

Artificial intelligence-driven automated lung sizing from chest radiographs.

Lung size measurements play an important role in transplantation, as optimal donor-recipient size ma...

Deep reinforcement learning control of combined chemotherapy and anti-angiogenic drug delivery for cancerous tumor treatment.

By virtue of the chronic and dangerous nature of cancer, researchers have explored various approache...