Pathology

Artificial intelligence in paediatric neuroradiology: current landscape, challenges, and future directions.

This narrative review maps the current landscape of artificial intelligence (AI) in paediatric and fetal neuroradiology, critically evaluating current practice, barriers to clinical adoption, and future potential. We searched for peer-reviewed studies from the last decade, focusing on image segmentation, lesion detection, classification, prognostication, and clinical decision support in paediatric...

Navigated hepatic tumor resection using intraoperative ultrasound imaging.

PURPOSE: This proof-of-concept study evaluates the feasibility and accuracy of an ultrasound-based navigation system for open liver surgery. Unlike most conventional systems that rely on registration to preoperative imaging, the proposed system provides navigation-guided resection using 3D models generated from intraoperative ultrasound. METHODS: A pilot study was conducted in 25 patients undergoi...

Biomechanics-informed Non-rigid Medical Image Registration with Elasticity Theories.

Biomechanical modelling of soft tissue provides a method for constraining medical image registration, such that the estimated spatial transformation i...

Real-time intraoperative confocal laser endomicroscopy with on-site neuropathologist consultation for glioma margin assessment: illustrative case.

BACKGROUND: Achieving maximal safe resection in glioma surgery requires accurate real-time margin assessment, yet existing technologies have limitatio...

Non-invasive differentiation of light chain amyloidosis and multiple myeloma based on Raman spectroscopy analysis using one-dimensional convolutional neural networks.

Light chain amyloidosis (AL) and multiple myeloma (MM) are interrelated plasma cell disorders characterized by malignant proliferation, yet they demon...

Machine learning and metabolic signatures of drowning: A pathway to uncovering cause of death in aquatic environments.

The postmortem diagnosis of drowning is challenging due to the nonspecific and transient nature of classical autopsy findings. This study aimed to inv...

Multivariate feature analysis of early-stage laryngeal cancer serum components using surface-enhanced Raman spectroscopy.

Laryngeal cancer is a common head-and-neck malignant tumor with geographically variable incidence. Its lack of specific early clinical symptoms often ...

A transformer and 3D CNN-based feature fusion network with interpretable ability for Raman spectra analysis: improving the diagnosis of thyroid cancer.

Accurate differentiation of benign and malignant thyroid lesions continues to pose a significant clinical challenge. Raman spectroscopy offers label-f...

Efficient self-supervised Barlow Twins from limited tissue slide cohorts for colonic pathology diagnostics.

Colorectal cancer (CRC) is one of the few cancers that have an established dysplasia-carcinoma sequence that benefits from screening. Everyone over 50...

MRI-based deep learning and radiomics for preoperative prediction of P53abn endometrial cancer: A multicenter study.

PURPOSE: To develop and validate a non-invasive magnetic resonance imaging (MRI)-based deep learning and radiomics approach for the preoperative diffe...

Research on Lung Cancer Classification Based on Multidimensional Hematological Indicators and Machine Learning Models.

Accurate subtyping of lung cancer is crucial for developing personalized treatment plans and improving patient outcomes. This study established machin...

Lactate metabolism-driven tumor heterogeneity and molecular signatures in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver malignancy with limited therapeutic options and poor prognosis. Recent ...

Noninvasive diagnosis of colorectal adenoma: The emerging potential of blood-based biomarkers.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related death globally. Most CRCs arise fro...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...

Moving Beyond Morphology: Toward a Morpho-Molecular Classification of Pleural Mesothelioma.

Despite recent advances in the treatment of pleural mesothelioma, it remains a challenging and heterogeneous disease, with limited options for patient...

Deciphering the air pollution-osteoarthritis relationship: insights from network toxicology, integrated machine learning, and molecular docking.

Mounting evidence suggests an association between air pollution and the pathogenesis of osteoarthritis (OA), yet the underlying molecular mechanisms r...

AI decision support for increasing prostate biopsy efficiency: a retrospective multicentre, multiscanner study.

OBJECTIVES: To develop and retrospectively validate an artificial intelligence-based decision support system (AI-DSS) for optimising prostate biopsy d...

Distinction Between Benign and Borderline/Malignant Phyllodes Tumor in Breast Mammography and Ultrasound Based on Radiomics Methods.

RATIONALE AND OBJECTIVES: This study aims to evaluate whether radiomics methods used on breast mammography (MG) and ultrasound (US) could distinguish ...

Single-cell transcriptomic analysis and machine learning identify ATAD3A as a key gene that stabilizes mitochondrial-endoplasmic reticulum membranes, promoting bladder cancer progression.

BACKGROUND: Mitochondria-associated endoplasmic reticulum membranes (MAM) play a critical regulatory role in cancer, yet their function in bladder can...

Deep learning-based H&E-derived risk scores in colorectal cancer: associations with tumour morphology, biology, and predicted drug response.

Over recent years, several deep learning (DL) models have been presented to predict colorectal cancer (CRC) patient survival directly from haematoxyli...