Pathology

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

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Microenvironmental information significantly improves the recognition of cell types in human lung cancer patients

Accurate single-cell phenotypic classification in histopathological tissue sections is essential for...

Post-operative tissue fragment puzzling using histopathological vision transformer alignment HiViTAlign

In pathology, reconstructing adjacent tissue parts enables an overview of the macro environment of o...

Holotomography-driven learning for in-silico staining of single cells in flow cytometry avoiding co-registration

Virtual staining is the current state-of-the-art computational technique to cleverly enhance intrace...

TU_MyCo-Vision: A Deep Learning Tool for Detection of Cell Morphologies in Fungal Microscopic Images

Morphological switching in response to environmental stimuli is a well-known phenomenon in fungi, le...

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability

The accurate prediction of chromosomal instability from the morphology of circulating tumor cells (C...

Deep-learning triage of 3D pathology datasets for comprehensive and efficient pathologist assessments

Standard-of-care slide-based 2D histopathology severely undersamples spatially heterogeneous tissue ...

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity

Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phen...

CanID: a robust and accurate RNAseq Expression-based diagnostic classification scheme for pediatric malignancies

Cancer subtype classification is critical for precision therapy and there is a growing trend of augm...

Powerful and accurate case-control analysis of spatial molecular data

As spatial molecular data grow in scope and resolution, there is a pressing need to identify key spa...

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision onc...

Colorectal cancer heterogeneity co-evolves with tumor architecture to determine disease outcome

Intratumoral heterogeneity, originating from genetic, epigenetic, and phenotypic cellular diversity,...

Detection of prostate cancer in 3D pathology datasets via generative immunolabeling

Recent advancements in nondestructive 3D pathology offer a complement to standard histology by enabl...

EpiPred: A gene-specific machine learning model for classifying missense variants in the epilepsy-related gene STXBP1

Missense variants in the STXBP1 gene are a frequent cause of early-onset developmental and epileptic...

TCUP – An Open Access Tool to Predict Tissue of Origin and Cancer of Unknown Primary (CUP)

Cancer of unknown primary (CUP) remains a major diagnostic hurdle, compromising therapies that depen...

TissueFormer: a neural network for labeling tissue from grouped single-cell RNA profiles

Single-cell RNA sequencing technologies have enabled unprecedented insights into gene expression and...

Conceptualization and Feasibility Testing of a Vibro-Acoustic Solution for Tumor Detection

Accurate detection of tumors is critical for the success of oncologic surgical intervention. Along w...

ESPWA: a deep learning-enabled tool for precision-based use of endocrine therapy in resource-limited settings

Cancer morbidity disproportionately affects patients in low- and middle-income countries (LMICs), wh...

Extracting biological structure and heterogeneity from the nano to the macro scale

Fluorescence microscopy is an essential tool in biology. It has revealed great variability at multip...

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