Pathology

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

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Hybrid convolutional neural network and bi-LSTM model with EfficientNet-B0 for high-accuracy breast cancer detection and classification.

Breast cancer detection remains one of the most challenging problems in medical imaging. We propose ...

Advancements in artificial intelligence for atopic dermatitis: diagnosis, treatment, and patient management.

Atopic dermatitis (AD) is a common and complex skin disease that significantly affects the quality o...

Fast, accurate, and versatile data analysis platform for the quantification of molecular spatiotemporal signals.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biologi...

NeuroNasal: Advanced AI-Driven Self-Supervised Learning Approach for Enhanced Sinonasal Pathology Detection.

Sinus diseases are inflammations or infections of the sinuses that significantly impact patient qual...

Pseudotargeted metabolomics profiles potential damage-associated molecular patterns as machine learning predictors for acute pancreatitis.

Acute pancreatitis (AP) is a common gastrointestinal disease characterized by pancreatic cell damage...

Integrated bioinformatics analysis to develop diagnostic models for malignant transformation of chronic proliferative diseases.

The combined analysis of dual diseases can provide new insights into pathogenic mechanisms, identify...

Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.

Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study...

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study.

BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalabi...

Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey.

Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenge...

Using artificial intelligence system for assisting the classification of breast ultrasound glandular tissue components in dense breast tissue.

To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound ana...

Emittance minimization for aberration correction I: Aberration correction of an electron microscope without knowing the aberration coefficients.

Precise alignment of the electron beam is critical for successful application of scanning transmissi...

Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles.

Autism spectrum disorder (ASD) presents significant challenges in diagnosis and intervention due to ...

Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy.

Monitoring and tracking of cell motion is a key component for understanding disease mechanisms and e...

Emittance minimization for aberration correction II: Physics-informed Bayesian optimization of an electron microscope.

Aberration-corrected Scanning Transmission Electron Microscopy (STEM) has become an essential tool i...

FACT: foundation model for assessing cancer tissue margins with mass spectrometry.

PURPOSE: Accurately classifying tissue margins during cancer surgeries is crucial for ensuring compl...

Multi-Scale Dynamic Sparse Token Multi-Instance Learning for Pathology Image Classification.

In many challenging breast cancer pathology images, the proportion of truly informative tumor region...

Self-Supervised Multi-Scale Multi-Modal Graph Pool Transformer for Sellar Region Tumor Diagnosis.

The sellar region tumor is a brain tumor that only exists in the brain sellar, which affects the cen...

Prior Visual-Guided Self-Supervised Learning Enables Color Vignetting Correction for High-Throughput Microscopic Imaging.

Vignetting constitutes a prevalent optical degradation that significantly compromises the quality of...

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