Pathology

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

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Diabetes diagnosis using a hybrid CNN LSTM MLP ensemble.

Diabetes is a chronic condition brought on by either an inability to use insulin effectively or a la...

Histology image analysis of 13 healthy tissues reveals molecular-histological correlations.

Gene expression is an important process in which genes guide the synthesis of proteins, and molecula...

Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning.

Forensic pathology plays a vital role in determining the cause and manner of death through macroscop...

Digital Pathology in Hematopathology: From Vision to Deployment.

Digital pathology (DP) has evolved alongside other technical advances, transforming our daily lives ...

Artificial Intelligence in digital pathology of breast cancer, new era of practice?

Breast cancer is the most common cancers among women worldwide. Early diagnosis and personalized med...

Diagnostic technologies for neuroblastoma.

Neuroblastoma is an aggressive childhood cancer characterised by high relapse rates and heterogenici...

Federated fault diagnosis method for collaborative self-diagnosis and cross-robot peer diagnosis.

In multi-robot collaboration, individual failures can propagate to other robots due to the topologic...

Accuracy and acceptability of self-sampling HPV testing in cervical cancer screening: a population-based study in rural Yunnan, China.

To evaluate the accuracy and acceptability of self-sampling samples for HPV testing for cervical can...

AI-Assisted Semiquantitative Measurement of Murine Bleomycin-Induced Lung Fibrosis Using In Vivo Micro-CT: An End-to-End Approach.

Small animal models are crucial for investigating idiopathic pulmonary fibrosis (IPF) and developing...

The Use of ChatGPT-4.0 to Simplify Breast Pathology Reports: A Study on Readability and Accuracy.

BACKGROUND: Patients have immediate access to their diagnostic reports but these reports exceed the ...

Automatic measuring of coronary atherosclerosis from medicolegal autopsy photographs based on deep learning techniques.

A diagnosis of atherosclerotic cardiovascular disease is critical importance in forensic medicine, p...

GraphCellNet: A deep learning method for integrated single-cell and spatial transcriptomic analysis with applications in development and disease.

Spatial transcriptomics (ST) integrates gene expression with spatial location, enabling precise mapp...

ViT-GCN: a novel hybrid model for accurate pneumonia diagnosis from x-ray images.

This study aims to enhance the accuracy of pneumonia diagnosis from x-ray images by developing a mod...

Application of machine learning reveals diagnostic biomarkers related to pyroptosis in Alzheimer's disease and analysis of immune infiltration.

BackgroundAlzheimer's disease (AD) is characterized by complex pathological mechanisms, with pyropto...

One-dimensional time-frequency dual-channel visual transformer for bearing fault diagnosis under strong noise and limited data conditions.

In industrial settings, bearing health directly affects equipment stability, making accurate and eff...

Identification of clinical diagnostic and immune cell infiltration characteristics of acute myocardial infarction with machine learning approach.

Acute myocardial infarction (AMI) is a serious heart disease with high fatality rates. The progress ...

Auto-embedding transformer under multi-source information fusion for few-shot fault diagnosis.

Data-driven intelligent fault diagnosis methods have become essential for ensuring the reliability a...

Significance of a Novel Angiogenesis-Related Biomarker Neuropilin-1 in Keloids.

Keloids are a severe type of pathological scars caused by excessive connective tissue hyperplasia af...

Computer vision to predict cell seeding coverage in re-endothelialized mouse lungs.

Transplantation of donor grafts recellularized with recipient-derived or non-immunogenic universal c...

2.5D Deep Learning-Based Prediction of Pathological Grading of Clear Cell Renal Cell Carcinoma Using Contrast-Enhanced CT: A Multicenter Study.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning model based on arterial phase-enha...

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