Anemia

Integrating multi-omics and machine learning systematically deciphers cellular heterogeneity and fibrotic regulatory networks in the progression from MASLD to MASH.

The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic d...

Robust multimodal mental workload classification: A cross-physiological condition machine learning approach.

BACKGROUND AND OBJECTIVE: Aircraft pilots can be faced with a high mental workload (MW) combined wit...

Programmable Smart CAR-T design: A new paradigm in precision immunotherapy driven by logic gates, conditional activation, allogeneic strategies, and artificial intelligence.

Chimeric antigen receptor T-cell (CAR-T) therapy has achieved unprecedented success in hematological...

Unraveling stress-adaptation pathways in cancer: Functional dissection through CRISPR-based genetic screens.

Cancer cells face a hostile microenvironment characterized by hypoxia, nutrient deprivation, endopla...

Impact of mobile phone use on the brain activity: Audio call vs video call.

The growing dependence on mobile phones for communication has raised concerns regarding the neurolog...

From PHQ-2 to PHQ-2W: Data-driven identification of depressed mood and fatigue for optimized weighted depression screening.

OBJECTIVE: This study aims to optimize depression screening tools through a data-driven approach, id...

Development of interfacial oxygen micro-nanobubble technology for hypoxia remediation: Machine-learning assisted optimization and mechanistic insights into sustained oxygen release.

Aquatic deoxygenation requires efficient and durable oxygenation strategies. Here, we developed a da...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vascula...

Development of Automated High-Throughput Digital Microscopy With Deep Learning for Enhanced Blood Smear Imaging.

A microscope is essential in scientific and medical research, enabling the magnification of specimen...

FFTNet: fNIRS-based frequency-enhanced patch network for driving fatigue detection.

Functional near-infrared spectroscopy (fNIRS), with its ability to directly measure cerebral hemodyn...

Integrative metabolomics and machine learning reveal diagnostic biomarkers for gelsenicine intoxication.

ETHNOPHARMACOLOGICAL RELEVANCE: Gelsemium elegans Benth. (G. elegans) is a highly toxic medicinal pl...

DGPCNet: anemia detection from multimodal palm, fingernails, and eye conjunctiva images using deep global pyramid convolutional network.

BACKGROUND: Anemia is one of the most common hematological disorders causing fatigue, increased vuln...

Pixel-scale satellite forecasting of cyanobacteria in Florida lakes.

Rapid proliferation of potentially toxin-producing cyanobacteria (cyanobacterial harmful algal bloom...

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster ...

The Application of Machine-Learning Algorithms for Multiclass Classification of Microcytic Anemia Revealed That a Minimum Required Number of Hematological Parameters Is Enough to Achieve High Diagnostic Accuracy.

INTRODUCTION: Thalassemia is a major global health concern, as declared by the World Health Organiza...

Advancing Anemia Detection With Deep Neural Networks: A Comparative Analysis of Training Strategies Using Conjunctival Images.

SET-DGCN: An end-to-end electroencephalography-based fatigue detection method for young drivers.

Driver fatigue poses a critical threat to global road safety, particularly among young drivers. Neve...

MSDA-Net: Multiscale Spatiotemporal Dual-Attention Network for EEG-Based Driver Fatigue Detection.

Driver fatigue poses a severe risk to road safety, contributing to approximately 20% of fatal accide...

Estimating the Causal Effect of Realistic Treatment Strategies Using Longitudinal Observational Data.

BackgroundReal-world data can inform health care decisions by allowing the evaluation of nuanced tre...

Apparent Diffusion Coefficient Magnetic Resonance Imaging as a Predictive Biomarker for Hypoxia, Treatment De-escalation, and Recurrence in Human Papillomavirus-Associated Oropharyngeal Cancer.

PURPOSE: To evaluate whether quantitative diffusion-weighted magnetic resonance imaging derived appa...

Machine Learning-Based Prediction of β-Thalassemia Trait Using Red Blood Cell Indices.

OBJECTIVES: Anemia is a significant global health concern, with hypochromic microcytic anemia being ...