Pathology

Multi-omics integration of TPX2 in prognostic prediction in resectable hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and mortality rates globally, significantly affecting patient prognosis and quality of life. Currently, predicting postoperative recurrence risk and survival in HCC patients remains challenging, as precise and effective quantitative indicators are lacking, limiting clinicians' ability to make individualized treatment decisions...

3D Quantification of Viral Transduction Efficiency in Living Human Retinal Organoids.

The development of therapeutics builds on testing their efficiency in vitro. To optimize gene therapies, for example, fluorescent reporters expressed by treated cells are typically utilized as readouts. Traditionally, their global fluorescence signal has been used as an estimate of transduction efficiency. However, analysis in individual cells within a living 3D tissue remains a challenge. Readout...

Analytical Comparison of Commonly Used Laboratory-Developed Tests for the Assessment of Ki-67 in Breast Carcinoma With an FDA-Approved Benchmark.

Ki-67 immunohistochemistry (IHC), a commonly used assay for breast cancer risk prognostication, has significant inter-laboratory heterogeneity. This s...

Multiscale-fusion models with genomic, topological and pathomic features to predict response to radiation therapy for non-small cell lung cancer patients.

Artificial intelligence models with biomarkers to predict treatment responses to radiation would be necessary to maximise the treatment outcomes of in...

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Un...

Artificial Intelligence Quantitation of Steatosis on Frozen Section Preimplant Slides Correlates with Some Liver Transplant Outcomes.

Introduction.Increased steatosis on preimplant liver frozen section is associated with delayed graft function and primary nonfunction. Efforts to stan...

Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current cli...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprece...

A lipid atlas of the human kidney.

Tissue atlases provide foundational knowledge on the cellular organization and molecular distributions across molecular classes and spatial scales. He...

Diagnostic accuracy of machine learning-based magnetic resonance imaging models in breast cancer classification: a systematic review and meta-analysis.

OBJECTIVE: This meta-analysis evaluates the diagnostic accuracy of machine learning (ML)-based magnetic resonance imaging (MRI) models in distinguishi...

Label-free diagnosis of lung cancer by Fourier transform infrared microspectroscopy coupled with domain adversarial learning.

Lung cancer is one of the most prevalent malignancies, characterized by high morbidity and mortality rates. Current diagnostic approaches primarily re...

Uncovering Image-Driven Subtypes with Distinct Pathology and Clinical Course in Autopsy-Confirmed Four Repeat Tauopathies.

OBJECTIVES: The four-repeat (4R) tauopathies are a group of neurodegenerative diseases, including progressive supranuclear palsy (PSP), corticobasal d...

Artificial intelligence-powered microscopy: Transforming the landscape of parasitology.

Microscopy and image analysis play a vital role in parasitology research; they are critical for identifying parasitic organisms and elucidating their ...

Machine learning is changing osteoporosis detection: an integrative review.

Machine learning drives osteoporosis detection and screening with higher clinical accuracy and accessibility than traditional osteoporosis screening t...

Robotic Central Pancreatectomy with Omental Pedicle Flap: Tactics and Tips.

BACKGROUND: Robotic central pancreatectomy is increasingly used for pre- or low-grade malignant tumors in the pancreatic body balancing preservation o...

Preoperative prediction model for benign and malignant gallbladder polyps on the basis of machine-learning algorithms.

BACKGROUND: This study aimed to differentiate between benign and malignant gallbladder polyps preoperatively by developing a prediction model integrat...

Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.

Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (...

Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment.

Head and neck squamous cell carcinoma (HNSCC) remains a globally prevalent malignancy with high morbidity and mortality. Despite therapeutic advances,...

The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer.

To investigate the diagnostic capability of multiple machine learning algorithms combined with intratumoral and peritumoral ultrasound radiomics model...

A method for spatial interpretation of weakly supervised deep learning models in computational pathology.

Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI). Weakly supervised learning of tile-level data is typic...