Hematology

Lymphoma

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

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Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes.

BACKGROUND: Insulin resistance, lipotoxicity, and mitochondrial dysfunction contribute to the pathog...

Machine learning-based models for advanced fibrosis in non-alcoholic steatohepatitis patients: A cohort study.

BACKGROUND: The global prevalence of non-alcoholic steatohepatitis (NASH) and its associated risk of...

The ethics of non-explainable artificial intelligence: an overview for clinical nurses.

Artificial intelligence (AI) is transforming healthcare by enhancing clinical decision-making, parti...

FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis.

Single-cell multi-omics technologies have revolutionized the study of cell states and functions by s...

Graph neural networks for single-cell omics data: a review of approaches and applications.

Rapid advancement of sequencing technologies now allows for the utilization of precise signals at si...

MMnc: multi-modal interpretable representation for non-coding RNA classification and class annotation.

MOTIVATION: As the biological roles and disease implications of non-coding RNAs continue to emerge, ...

Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery.

PURPOSE: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PI...

[A review of deep learning methods for non-contact heart rate measurement based on facial videos].

Heart rate is a crucial indicator of human health with significant physiological importance. Traditi...

Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer.

IMPORTANCE: Only a small fraction of patients with advanced non-small cell lung cancer (NSCLC) respo...

Large language models in oncology: a review.

Large language models (LLMs) have demonstrated emergent human-like capabilities in natural language ...

Optimization of non-smooth functions via differentiable surrogates.

Mathematical optimization is fundamental across many scientific and engineering applications. While ...

Early prediction of colorectal adenoma risk: leveraging large-language model for clinical electronic medical record data.

OBJECTIVE: To develop a non-invasive, radiation-free model for early colorectal adenoma prediction u...

Exploring the suitability of piecewise-linear dynamical system models for cognitive neural dynamics.

Dynamical system models have proven useful for decoding the current brain state from neural activity...

Diagnostic precision of a deep learning algorithm for the classification of non-contrast brain CT reports.

OBJECTIVE: This study aimed to determine the diagnostic precision of a deep learning algorithm for t...

IDNet: An inception-like deformable non-local network for projection compensation over non-flat textured surfaces.

Projector compensation on non-flat, textured surfaces represents a formidable challenge in computati...

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