Pathology

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

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A generalist deep-learning volume segmentation tool for volume electron microscopy of biological samples.

We present the Volume Segmentation Tool (VST), a deep learning software tool that implements volumet...

CT-Based Radiomics for Predicting PD-L1 Expression in Non-small Cell Lung Cancer: A Systematic Review and Meta-analysis.

BACKGROUND AND PURPOSE: The efficacy of immunotherapy in non-small cell lung cancer (NSCLC) is intri...

A visual-omics foundation model to bridge histopathology with spatial transcriptomics.

Artificial intelligence has revolutionized computational biology. Recent developments in omics techn...

An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolution.

High-quality whole-slide scanning is expensive, complex, and time-consuming, thus limiting the acqui...

Recent Advances in Applications of Machine Learning in Cervical Cancer Research: A Focus on Prediction Models.

Artificial intelligence (AI) and machine learning (ML) are transforming cervical cancer research and...

Predicting NSCLC surgical outcomes using deep learning on histopathological images: development and multi-omics validation of Sr-PPS model.

BACKGROUND: Currently, there remains a critical need for reliable tools to accurately predict post-s...

Deep learning enables fast and accurate quantification of MRI-guided near-infrared spectral tomography for breast cancer diagnosis.

The utilization of magnetic resonance (MR) im-aging to guide near-infrared spectral tomography (NIRS...

The use of imaging in the diagnosis and treatment of thromboembolic pulmonary hypertension.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a potentially life-threatening condition, c...

CervicalMethDx: a precision DNA methylation test to identify risk of high-grade intraepithelial lesions in cervical cancer screening algorithms.

Cervical cancer is one of the most common cancers in women. Despite progress in prevention and succe...

Pathomics in Gastrointestinal Tumors: Research Progress and Clinical Applications.

Gastrointestinal tumors are among the malignancies with the highest global incidence and mortality r...

Hyperspectral imaging to characterize the vegetative tissue biochemical changes in response to water deficit conditions in sorghum ().

Hyperspectral imaging has been used to determine plant stress status. However, the biological interp...

Harnessing GPT-4 for automated error detection in pathology reports: Implications for oncology diagnostics.

OBJECTIVE: Accurate pathology reports are crucial for the diagnosis and treatment planning of cancer...

Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms.

Breast cancer is a significant health issue for women, characterized by its high rates of mortality ...

Multimodal Machine Learning Analysis of GaSe Molecular Beam Epitaxy Growth Conditions.

Autonomous synthesis platforms integrating machine learning with in situ diagnostics have the potent...

Deep learning for predicting invasive recurrence of ductal carcinoma in situ: leveraging histopathology images and clinical features.

BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to ipsilateral invasive breast cancer (IBC)...

Computed Tomography-Based Radiomics Diagnostic Model for Fat-Poor Small Renal Tumor Subtypes.

Differentiating histologic subtypes of fat-poor small renal masses using conventional imaging remai...

Cancer in a drop: Advances in liquid biopsy in 2024.

Over the past decade, liquid biopsy (LB) has emerged as a key tool in oncology. Its utility in non-i...

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