Hematology

Lymphoma

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

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A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulat...

Diagnostic modalities in the mediastinum and the role of bronchoscopy in mediastinal assessment: a narrative review.

BACKGROUND AND OBJECTIVE: Diagnosis of pathology in the mediastinum has proven quite challenging, gi...

Machine Learning Guided Rational Design of a Non-Heme Iron-Based Lysine Dioxygenase Improves its Total Turnover Number.

Highly selective C-H functionalization remains an ongoing challenge in organic synthetic methodologi...

Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.

BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long duration...

A multi-view prognostic model for diffuse large B-cell lymphoma based on kernel canonical correlation analysis and support vector machine.

BACKGROUND AND OBJECTIVE: Positron emission tomography/computed tomography (PET/CT) is recommended a...

AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease Using Novel Non-Invasive Biomarkers.

Coronary artery disease (CAD) is one of the most common causes of sudden cardiac arrest, accounting ...

Diagnostic Performance of Artificial Intelligence-Based Angiography-Derived Non-Hyperemic Pressure Ratio Using Pressure Wire as Reference.

BACKGROUND: The angiography-derived non-hyperemic pressure ratio (angioNHPR) is a novel index of NHP...

Development of a visuo-tactile sensor for non-destructive peach firmness and contact force measurement suitable for robotic arm applications.

Precise measurement of firmness was crucial for determining optimal harvesting times, implementing r...

A non-linear modelling approach to predict the dissolution profile of extended-release tablets.

This study proposes a novel non-linear modelling approach to predict the dissolution profiles of ext...

Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Stroke is a neurological complication that can occur in patients admitted to the intensive care unit...

Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques.

Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable...

Towards Dataset-Scale and Feature-Oriented Evaluation of Text Summarization in Large Language Model Prompts.

Recent advancements in Large Language Models (LLMs) and Prompt Engineering have made chatbot customi...

Automated workflow for the cell cycle analysis of (non-)adherent cells using a machine learning approach.

Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer res...

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