Pathology

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

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Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets.

Shoulder X-ray images typically have low contrast and high noise levels, making it challenging to di...

Class-aware multi-level attention learning for semi-supervised breast cancer diagnosis under imbalanced label distribution.

Breast cancer affects a significant number of patients worldwide, and early diagnosis is critical fo...

Chan-Vese aided fuzzy C-means approach for whole breast and fibroglandular tissue segmentation: Preliminary application to real-world breast MRI.

BACKGROUND: Magnetic resonance imaging (MRI) is a highly sensitive modality for diagnosing breast ca...

Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes.

Citrullination is a critical yet understudied post-translational modification (PTM) implicated in va...

Cross-ViT based benign and malignant classification of pulmonary nodules.

The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosi...

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning.

BACKGROUND: Early diagnosis of depression is crucial, and speech-based early diagnosis of depression...

Deep Learning and Single-Molecule Localization Microscopy Reveal Nanoscopic Dynamics of DNA Entanglement Loci.

Understanding molecular dynamics at the nanoscale remains challenging due to limitations in the temp...

Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer.

Gastric cancer (GC) is one of the most common tumors; one of the reasons for its poor prognosis is t...

Computer-aided cholelithiasis diagnosis using explainable convolutional neural network.

Accurate and precise identification of cholelithiasis is essential for saving the lives of millions ...

ThyroNet-X4 genesis: an advanced deep learning model for auxiliary diagnosis of thyroid nodules' malignancy.

Thyroid nodules are a common endocrine condition, and accurate differentiation between benign and ma...

Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques.

In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and ma...

Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images.

Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increase...

GobletNet: Wavelet-Based High-Frequency Fusion Network for Semantic Segmentation of Electron Microscopy Images.

Semantic segmentation of electron microscopy (EM) images is crucial for nanoscale analysis. With the...

IPNet: An Interpretable Network With Progressive Loss for Whole-Stage Colorectal Disease Diagnosis.

Colorectal cancer plays a dominant role in cancer-related deaths, primarily due to the absence of ob...

A Multi-Perspective Self-Supervised Generative Adversarial Network for FS to FFPE Stain Transfer.

In clinical practice, frozen section (FS) images can be utilized to obtain the immediate pathologica...

GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentation.

Histopathological image segmentation is a laborious and time-intensive task, often requiring analysi...

Radiomics Analysis of Different Machine Learning Models based on Multiparametric MRI to Identify Benign and Malignant Testicular Lesions.

RATIONALE AND OBJECTIVES: To develop and validate a machine learning-based prediction model for the ...

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