Hematology

Lymphoma

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

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Non-destructive identification of from different geographical origins by Vis/NIR and SWIR hyperspectral imaging techniques.

The composition of (Tai-Zi-Shen, TZS) is greatly influenced by the growing area of the plants, maki...

characterization and molecular epidemiology of spp. isolates from non-HIV patients in Guangdong, China.

BACKGROUND: The burden of cryptococcosis in mainland China is enormous. However, the characterizati...

Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.

BACKGROUND: This study aimed to develop and validate radiomics and deep learning (DL) signatures for...

Use of deep learning for the classification of hyperplastic lymph node and common subtypes of canine lymphomas: a preliminary study.

Artificial Intelligence has observed significant growth in its ability to classify different types o...

Model-based estimation of AV-nodal refractory period and conduction delay trends from ECG.

Atrial fibrillation (AF) is the most common arrhythmia, associated with significant burdens to pati...

Unsupervised SoftOtsuNet Augmentation for Clinical Dermatology Image Classifiers.

Data Augmentation is a crucial tool in the Machine Learning (ML) toolbox because it can extract nove...

Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.

This study focused on a novel strategy that combines deep learning and radiomics to predict epiderma...

Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis.

BACKGROUND: Accurate diagnosis and early treatment are essential in the fight against lymphatic canc...

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas.

Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ens...

Biomarkers and molecular endotypes of sarcoidosis: lessons from omics and non-omics studies.

Sarcoidosis is a chronic granulomatous disorder characterized by unknown etiology, undetermined mech...

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, ...

A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer.

BACKGROUND: To establish a predictive model based on multisequence magnetic resonance imaging (MRI) ...

Link prediction based on spectral analysis.

Link prediction in complex network is an important issue in network science. Recently, various struc...

Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives.

The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a ...

Predicting Phase 1 Lymphoma Clinical Trial Durations Using Machine Learning: An In-Depth Analysis and Broad Application Insights.

Lymphoma diagnoses in the US are substantial, with an estimated 89,380 new cases in 2023, necessitat...

Dr. GAI: Significance of Generative AI in Plastic Surgery.

In this letter to the editor, I offer a critique of the article titled "Consulting the Digital Docto...

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