Leukemia

Association of [F]-FDG PET/CT-Derived Radiomic Features with Clinical Outcomes and Genomic Profiles in Patients with Chronic Lymphocytic Leukemia.

The role of PET/CT imaging in chronic lymphoproliferative syndromes (CLL) is debated. This study examines the potential of PET/CT radiomics in predicting outcomes and genetic profiles in CLL patients. A retrospective analysis was conducted on 50 CLL patients treated at Policlinico Tor Vergata, Rome, and screened, at diagnosis, with [F]-FDG PET/CT. Potentially pathological lymph nodes were semi-a...

Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends.

The investigation and diagnosis of hematologic malignancy using blood cell image analysis are major and emerging subjects that lie at the intersection of artificial intelligence and medical research. This survey systematically examines the state-of-the-art in blood cancer detection through image-based analysis, aimed at identifying the most effective computational strategies and highlighting emerg...

Clinical Validation and Post-Implementation Performance Monitoring of a Neural Network-Assisted Approach for Detecting Chronic Lymphocytic Leukemia Minimal Residual Disease by Flow Cytometry.

: Flow cytometric detection of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL) is complex, time-consuming, and subject to inter-o...

Construction of Sonosensitizer-Drug Co-Assembly Based on Deep Learning Method.

Drug co-assemblies have attracted extensive attention due to their advantages of easy preparation, adjustable performance and drug component co-delive...

Artificial Intelligence and Data Science Methods for Automatic Detection of White Blood Cells in Images.

Data scieQuerynce (DS) methods and artificial intelligence (AI) are critical in today's healthcare services operations. This study focuses on evaluati...

Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI.

The preoperative human epidermal growth factor receptor type 2 (HER2) status of breast cancer is typically determined by pathological examination of a...

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persists after revascularization due to reperfusion inju...

Effects of Hepatic or Renal Impairment on Pharmacokinetics of Fruquintinib.

Fruquintinib (FRUZAQLA) is a highly selective tyrosine kinase inhibitor of all three vascular endothelial growth factor receptors (-1, -2, and -3). Tw...

Association of Physical Activity from Wearable Devices and Chronic Disease Risk: Insights from the All of Us Research Program.

Physical activity is a modifiable factor influencing chronic disease risk. Previous studies often relied on self-reported activity measures or short-t...

Mechanisms involved in pro-inflammatory responses to traffic-derived particulate matter (PM) in THP-1 macrophages compared to HBEC3-KT bronchial epithelial cells.

The pro-inflammatory responses in THP-1-derived macrophages and human bronchial epithelial cells (HBEC3-KT) were examined after exposure to size-fract...

Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence.

Acute myeloid leukemia (AML) is a severe hematological malignancy characterized by high recurrence rates, especially in pediatric patients, highlighti...

Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.

BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatmen...

Identification of Npas4 as a biomarker for CICI by transcriptomics combined with bioinformatics and machine learning approaches.

Chemotherapy is one of the most successful strategies for treating cancer. Unfortunately, up to 70 % of cancer survivors develop cognitive impairment ...

An efficient patient's response predicting system using multi-scale dilated ensemble network framework with optimization strategy.

The forecasting of a patient's response to radiotherapy and the likelihood of experiencing harmful long-term health impacts would considerably enhance...

Evaluation of Artificial Intelligence Models for Nutritional Symptom Management in Breast Cancer Patients Undergoing Chemotherapy.

The purpose of the study is to determine if artificial intelligence (AI) models could provide dietary recommendations to manage chemotherapy-induced n...

Artificial intelligence-based muscle analysis risk assessment of treatment-related toxicity in metastatic colorectal cancer.

IntroductionUp to 60% of adults with metastatic colorectal cancer (mCRC) receiving combination cytotoxic chemotherapy may experience loss of skeletal ...

Machine learning-based optimization of cytotoxicity testing for assessing Zn-based biodegradable metals.

Zinc (Zn)-based biodegradable metals are emerging as promising candidates for biomedical implants. Nonetheless, discrepancies between and biocompati...

Machine learning approach to single cell transcriptomic analysis of Sjogren's disease reveals altered activation states of B and T lymphocytes.

Sjogren's Disease (SjD) is an autoimmune disorder characterized by salivary and lacrimal gland dysfunction and immune cell infiltration leading to gla...

Forecasting optimal treatments in relapsed/refractory mature T- and NK-cell lymphomas: A global PETAL Consortium study.

There is no standard of care in relapsed/refractory T-cell/natural killer-cell lymphomas. Patients often cycle through cytotoxic chemotherapy (CC), ep...

Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics.

Single-cell proteomics is a pivotal technology for studying cellular phenotypes, offering unparalleled insights into cellular heterogeneity and dynami...