Pathology

From accuracy to service: deciding what artificial intelligence outputs may do in veterinary diagnostic laboratories.

Artificial intelligence (AI) tools are entering veterinary diagnostic laboratory service, but reported model accuracy does not determine what the laboratory staff should allow an output to do. This Commentary defines service entry as the point at which an AI output is allowed to influence case triage, interpretation, a draft report, or result release. Before that point, the laboratory staff should...

Development and validation of a multidimensional machine learning model for predicting delayed graft function in deceased donor kidney transplantation.

PURPOSE: Delayed graft function (DGF) remains a significant complication following deceased donor kidney transplantation. This study aimed to develop and validate a multidimensional machine learning model for predicting DGF by integrating clinical data, machine perfusion parameters, donor scores, and histopathological scores. METHODS: A retrospective analysis was conducted on 961 deceased donor ki...

Multimodal artificial intelligence in prostate cancer: integrating multiparametric MRI with clinicopathological, molecular, and functional imaging data.

Multimodal artificial intelligence (AI) is reshaping prostate cancer imaging by moving beyond MRI-only algorithms toward models that integrate multipa...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy.

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...

Merging artificial intelligence and retinal vascular geometric parameters: A novel tool for diagnosis and prognosis prediction of diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. The retinal microvasculature, as the only directly observable m...

HisToSpatialCNV: an interpretable deep learning method predicting spatial copy number variations from histopathology images.

Copy number variations (CNV) are key drivers of cancer progression, yet methods for predicting spatial CNVs directly from haematoxylin and eosin (H&E)...

Multidimensional 5-hydroxymethylcytosine features in cell-free DNA enable the detection, staging and subtyping of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignant cancer with limited biomarkers for early detection and disease stratification. He...

AI for tumour proportion scoring of programmed death-ligand 1 immunohistochemistry in non-small cell lung cancer: a review of commercial and non-commercial tools.

Programmed death-ligand 1 (PD-L1) expression, commonly quantified as tumour proportion score (TPS), is a key biomarker guiding immunotherapy in non-sm...

EffiSegNet: Advances in Automated Segmentation of Actinic Cheilitis and Lip Squamous Cell Carcinoma in Clinical Photographs.

BACKGROUND: Actinic cheilitis (AC) is a potentially malignant oral disorder linked to lip squamous cell carcinoma (LSCC). Clinical diagnosis is hinder...

Deep Learning-Based Classification of In Vivo Embryonic Development Stages in Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) Using Real-Time Microscopy Images.

Accurate staging of embryonic development is crucial for applied studies that require precise determination of embryonic age, such as developmental bi...

Comparative Performance of Multimodal Large Language Models in Grayscale Ultrasound-Based Classification of Thyroid Nodules.

BACKGROUND: Multimodal large language models (LLMs) are increasingly being explored for medical image analysis, but their relative performance in thyr...

Super-resolution MRI and 2.5D deep learning for intratumoral-peritumoral radiomics in preoperative prediction of rectal cancer perineural invasion.

OBJECTIVES: Preoperative prediction of perineural invasion (PNI) in rectal cancer (RC) is challenging due to limited MRI resolution and the neglect of...

Digital Biobanking in the Era of Artificial Intelligence.

The terminology "Biobank" is used for the organized collection of biological materials consisting of tissue samples, blood, serum, body fluids, and DN...

Predicting PD-L1+ CD8- status in NSCLC tissue from clinical indicators using machine learning.

BACKGROUND: Programmed death-ligand 1 (PD-L1) expression and CD8-positive (CD8+) T-cell infiltration in tumor tissue are associated with prognosis in ...

A drift-aware framework for reliability assessment and image-based interpretation of atomic force microscopy measurements.

Drift is one of the primary sources of uncertainty limiting the accuracy, repeatability, and reliability of scanning probe microscopy (SPM) measuremen...

Comparative evaluation of feature-selection strategies for machine learning-based histological grading of breast cancer using tumor and fibroglandular-tissue DCE-MRI features.

BACKGROUND: Nottingham histological grading is central to breast cancer prognosis and treatment planning, but conventional pathological assessment is ...

Bile extracellular vesicles for early cholangiocarcinoma detection in primary sclerosing cholangitis.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA) is a major complication of primary sclerosing cholangitis (PSC), with a 20-year incidence of ∼15%. Early d...

A deep learning-derived risk score model from digital pathology to forecast nivolumab outcomes in gastric carcinoma.

BACKGROUND: The PD-L1 combined positive score (CPS) is a biomarker predicting responses in gastric cancer (GC) immunotherapy. OBJECTIVES: We aimed to ...

Integrated Transcriptomic Analysis and Machine Learning Identify THY1 as a Key Regulator of Cancer-Associated Fibroblast Infiltration, Promoting Malignant Progression and Immune Escape in Gastric Cancer.

BACKGROUND: Heterogeneity in cancer-associated fibroblast (CAF) infiltration within the tumor microenvironment is closely associated with gastric canc...

RNA splicing in health and disease.

RNA splicing expands the functional output of eukaryotic genomes by enabling individual precursor messenger RNA (pre-mRNA) to generate multiple mature...