Pathology

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

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Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but t...

CPU-READY DEEP LEARNING APPROACH FOR ROBUST TISSUE REGION SEGMENTATION ACROSS MULTI-COHORT H&E AND IHC-STAINED WHOLE SLIDE IMAGES

With the rise of digital pathology, integrating digital slides with deep learning–based decision sup...

Prognostic role of COVID-19 pneumonia signs and other CT-biomarkers for survival in patients with malignant neoplasms: the ARILUS project

Clinically manifested pneumonia associated with COVID-19 infection in cancer patients has been assoc...

Improving automated prostate pathological grading via confidence filtering

There have been many promising developments in deep learning to identify degrees of malignancies in ...

Intraoperative classification of glioblastoma through near real-time stimulated Raman scattering microscopy

Glioblastoma is a highly malignant brain tumor in which maximal safe resection is associated with im...

Predicting Methylation-Based Replication Timing from Whole Slide Images

Replication timing is a costly but powerful tool for characterizing cellular mechanisms that underli...

On Estimating Age and Gender from Parkinson’s Disease Diagnostic-Oriented Recordings Using Wav2Vec 2.0

Can self-supervised speech foundation models (SFMs) be used for automatic patient metadata extractio...

Learning Patient Similarity from Genomics for Precision Oncology

Precision oncology has informed cancer care by enabling the discovery and application of diagnostic,...

Pathology’s Last Exam: Stress-Testing Diagnostic Reasoning and Safety in Large Language Models

Large language models (LLMs) are evolving into diagnostic co-pilots, yet current benchmarks fail to ...

IHGAMP: Pan-cancer HRD prediction from routine H&E whole-slide images using foundation models

Homologous recombination deficiency (HRD) confers sensitivity to poly (ADP-ribose) polymerase (PARP)...

Morphological Landscape Mapping Decodes Pathological Heterogeneity and Proteomic Programs in HCC

Intratumour heterogeneity (ITH) drives the clinical trajectory of HCC, yet routine pathology relies ...

Mechanosensitive TRPV4 immunohistochemistry improves deep learning-based grading of ductal carcinoma in situ beyond H&E morphology

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer spanning a biologic continuum from a...

CrosSplice: A Pipeline for Identifying Rare Splice-Site Creating Variants from Cross-Tissue Transcriptome Data

Despite their profound impact on patients’ lives, most rare and intractable diseases still lack esta...

High Consistency, Limited Accuracy: Evaluating Large Language Models for Binary Medical Diagnosis

Large Language Models (LLMs) have demonstrated impressive capabilities in medical knowledge tasks, a...

Exploring Machine Learning Models to Uncover Pathways in ALS Pathogenesis Using Immunohistochemical Features

Amyotrophic Lateral Sclerosis (ALS) is a degenerative disease of motor neurons that leads to muscle ...

OpenSlideFM: A Computationally Efficient Multi-Scale Foundation Model for Computational Pathology

Computational pathology increasingly relies on foundation models pre-trained on large-scale histopat...

Erythrogram directly from the microscope eyepiece: a feasibility study using artificial intelligence

Erythrocyte indices are essential for the diagnosis and monitoring of hematologic diseases, but thei...

A method for lung cancer detection and staging from a drop of blood plasma via Raman spectroscopy of well-based samples (ROWS)

We present a new method for lung pathology detection in blood plasma, including lung cancer staging....

The SMART-AI trial: Real-time cholangioscopy artificial intelligence for the classification of biliary strictures

Sampling techniques have poor accuracy for classifying biliary strictures as benign or malignant. Pr...

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