Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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A CNN-transformer fusion network for predicting high-grade patterns in stage IA invasive lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma (LUAD) with the high-grade patterns (HGPs) has the potentia...

Predictive models of epidermal growth factor receptor mutation in lung adenocarcinoma using PET/CT-based radiomics features.

BACKGROUND: Lung adenocarcinoma (LAC) comprises a substantial subset of non-small cell lung cancer (...

Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.

PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lun...

Enhancing cell instance segmentation in scanning electron microscopy images via a deep contour closing operator.

Accurately segmenting and individualizing cells in scanning electron microscopy (SEM) images is a hi...

Enhancing synchrotron radiation micro-CT images using deep learning: an application of Noise2Inverse on bone imaging.

In bone-imaging research, in situ synchrotron radiation micro-computed tomography (SRµCT) mechanical...

Deep Learning-driven Microfluidic-SERS to Characterize the Heterogeneity in Exosomes for Classifying Non-Small Cell Lung Cancer Subtypes.

Lung cancer exhibits strong heterogeneity, and its early diagnosis and precise subtyping are of grea...

Identifying chemotherapy beneficiaries in nasal and paranasal sinus cancers: epidemiological trends and machine learning insights.

BACKGROUND: Studies on the epidemiological characteristics, treatment strategies and prognosis of na...

Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma.

The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC)...

A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection.

The most widespread kind of cancer, affecting millions of lives is skin cancer. When the condition o...

Improved gated recurrent unit-based osteosarcoma prediction on histology images: a meta-heuristic-oriented optimization concept.

The major prevalent primary bone cancer is osteosarcoma. Preoperative chemotherapy is accompanied by...

Taking the 3Rs to a higher level: replacement and reduction of animal testing in life sciences in space research.

Human settlements on the Moon, crewed missions to Mars and space tourism will become a reality in th...

Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach.

BACKGROUND: Non-small-cell lung cancer (NSCLC) and its surgery significantly increase the venous thr...

A novel hybrid feature fusion approach using handcrafted features with transfer learning model for enhanced skin cancer classification.

Skin cancer is a deadly disease and has the highest rising rates globally. It arises from aberrant s...

Deep learning-based breast MRI for predicting axillary lymph node metastasis: a systematic review and meta-analysis.

BACKGROUND: To perform a systematic review and meta-analysis that assesses the diagnostic performanc...

Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study.

BACKGROUND: Microvascular invasion (MVI) is an important risk factor for early postoperative recurre...

Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.

Pancreatic cancer (PC) is a fatal disease with an extremely low 5-year survival rate, mainly because...

Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens.

Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological charact...

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