Pathology

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

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Artificial intelligence to enhance the diagnosis of ocular surface squamous neoplasia.

To provide an artificial intelligence (AI) method using in vivo confocal microscopy (IVCM) to differ...

Microscope Upcycling: Transforming legacy microscopes into automated cloud-integrated imaging systems.

Computerized microscopes improve repeatability, throughput, antisepsis, data analysis and data shari...

Artificial Intelligence and Convolutional Neural Networks-Driven Detection of Micro and Macro Metastasis of Cutaneous Melanoma to the Lymph Nodes.

BACKGROUND: Lymph node (LN) assessment is a critical component in the staging and management of cuta...

Weighted Multi-Modal Contrastive Learning Based Hybrid Network for Alzheimer's Disease Diagnosis.

Multiple imaging modalities and specific proteins in the cerebrospinal fluid, providing a comprehens...

TriDeNT : Triple deep network training for privileged knowledge distillation in histopathology.

Computational pathology models rarely utilise data that will not be available for inference. This me...

Complex wound analysis using AI.

Impaired wound healing is a significant clinical challenge. Standard wound analysis approaches are m...

AI-driven framework to map the brain metabolome in three dimensions.

High-resolution spatial imaging is transforming our understanding of foundational biology. Spatial m...

A semi-supervised convolutional neural network for diagnosis of pancreatic ductal adenocarcinoma based on EUS-FNA cytological images.

BACKGROUND: The cytological diagnostic process of EUS-FNA smears is time-consuming and manpower-inte...

Deep learning based on intratumoral heterogeneity predicts histopathologic grade of hepatocellular carcinoma.

OBJECTIVES: The potential of medical imaging to non-invasively assess intratumoral heterogeneity (IT...

Design and application of ISSA-BP neural network model for predicting soft tissue relaxation force.

: Accurate biomechanical modeling is crucial for enhancing the realism of virtual surgical training....

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its...

ECP-GAN: Generating Endometrial Cancer Pathology Images and Segmentation Labels via Two-Stage Generative Adversarial Networks.

BACKGROUND: Endometrial cancer is one of the most common tumors of the female reproductive system an...

Histopathology image classification based on semantic correlation clustering domain adaptation.

Deep learning has been successfully applied to histopathology image classification tasks. However, t...

Reduction of Acquisition Time in Fourier Transform Infrared Spectral Imaging by Deep Learning for Clinical Applications.

In infrared Fourier transform spectral imaging applied to biomedical challenges, data quality is of ...

Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.

Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) ...

Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study.

BACKGROUND: Machine learning (ML) is a significant area of artificial intelligence, which can improv...

Deep Learning for High Speed Optical Coherence Elastography With a Fiber Scanning Endoscope.

Tissue stiffness is related to soft tissue pathologies and can be assessed through palpation or via ...

CoD-MIL: Chain-of-Diagnosis Prompting Multiple Instance Learning for Whole Slide Image Classification.

Multiple instance learning (MIL) has emerged as a prominent paradigm for processing the whole slide ...

Defining lipedema's molecular hallmarks by multi-omics approach for disease prediction in women.

Lipedema is a chronic disease in females characterized by pathologic subcutaneous adipose tissue exp...

Light scattering imaging modal expansion cytometry for label-free single-cell analysis with deep learning.

BACKGROUND AND OBJECTIVE: Single-cell imaging plays a key role in various fields, including drug dev...

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