Pathology

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

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Neural Networks as Entropic Systems: Applications in Digital Pathology

Deep learning systems in digital pathology are widely regarded as opaque, limiting clinical trust an...

MLMarker: A machine learning framework for tissue inference and biomarker discovery

MLMarker is a machine learning tool that computes continuous tissue similarity scores for proteomics...

Toxicity Assessment in Preclinical Histopathology via Class-Aware Mahalanobis Distance for Known and Novel Anomalies

Drug-induced toxicity remains a leading cause of failure in preclinical development and early clinic...

Effectiveness of Automatically Curated Dataset in Thyroid Nodules Classification Algorithms Using Deep Learning

The diagnosis of thyroid nodule cancers commonly utilizes ultrasound images. Several studies showed ...

Tissue-to-Analysis Framework Enables Multiscale Mapping of the Architectural and Cellular Organization in the Human Dorsal Root Ganglion

Transcriptomic studies have helped us understand the dorsal root ganglia's cellular milieu, yet our ...

AI quantification of inflammatory and architectural features in ulcerative colitis distinguishes active disease from remission

Background and Aims: Artificial intelligence (AI) is increasingly applied to histological assessment...

A multimodal AI biomarker PATH-ORACLE improves prediction of recurrence in stage I lung adenocarcinoma

The standard treatment for stage I lung adenocarcinoma is surgical resection, in most cases without ...

clinTALL: machine learning-driven multimodal subtypeclassification and treatment outcome prediction in pediatric T-ALL

Background: Childhood T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic ma...

HistoPrism: Unlocking Functional Pathway Analysis from Pan-Cancer Histology via Gene Expression Prediction

Predicting spatial gene expression from H&E histology offers a scalable and clinically accessible al...

Machine Learning Ensemble Reveals Distinct Molecular Pathways of Retinal Damage in Spaceflown Mice

Spaceflight-associated neuro-ocular syndrome (SANS) threatens astronaut health during long-duration ...

HistoPrism: Unlocking Functional Pathway Analysis from Pan-Cancer Histology via Gene Expression Prediction

Predicting spatial gene expression from H&E histology offers a scalable and clinically accessible al...

Multimodal Visual Surrogate Compression for Alzheimer's Disease Classification

High-dimensional structural MRI (sMRI) images are widely used for Alzheimer's Disease (AD) diagnosis...

Global mRNA 3'UTR lengthening in small-cell neuroendocrine carcinoma

Small-cell neuroendocrine carcinoma (SCNC) is a rare but highly malignant tumor subtype that primari...

Evaluating Spiking and Non-Spiking Neural Networks for Colorectal Serrated Polyp Subtype Classification

Image classification on digital pathology images relies heavily on convolutional neural networks (CN...

Automated HER2 scoring with uncertainty quantification using lensfree holography and deep learning

Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression is critical for br...

The marine microbiome can accurately predict its chemical and biological environment

The microbiome responds to physicochemical changes in the environment, making it a sensitive indicat...

SpatialDINO: A Self-Supervised 3D Vision Transformer that enables Segmentation and Tracking in Crowded Cellular Environments

Quantitative, time-resolved 3D fluorescence microscopy can reveal complex cellular dynamics in livin...

High-fidelity bioimage restoration via adversarial learning

Live-cell microscopy restoration is constrained by a trade-off between inference latency and texture...

A Mobile AI-enhanced Platform for Standardized Wound Assessment and Clinical Decision Support

Chronic wounds affect over 1.2 million Canadians and incur healthcare costs exceeding $13 billion an...

VISTA-PATH: An interactive foundation model for pathology image segmentation and quantitative analysis in computational pathology

Accurate semantic segmentation for histopathology image is crucial for quantitative tissue analysis ...

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