Pathology

Machine learning using entropy-based texture features from MRI to differentiate histological subtypes of non-small cell lung cancer identified as metabolically active on PET/MRI.

Texture analysis is a foundational approach in imaging studies and demonstrates excellent diagnostic performance, with radiomic analysis being the most widely used method. New approaches to texture analysis continue to be developed. However, magnetic resonance imaging (MRI)-based radiomics studies for identifying histological subtypes of lung cancer remain scarce. This study aimed to improve the e...

Atypical Histology in Pulmonary Biopsies Obtained Using Robotic-Assisted Bronchoscopy: Natural History and Clinical Practice.

BACKGROUND: A recent consensus statement recommends that atypical cells are considered nondiagnostic specimens in the calculation of diagnostic yield. This study investigated the natural history and malignancy rate of atypical cells and practice patterns of clinicians encountering these biopsy results. METHODS: This was a subset analysis of a prospective, multicenter study evaluating the safety an...

Development and validation of an Interpretable Machine learning model for Discriminating between benign and malignant breast cancer.

OBJECTIVE: Breast cancer prognosis depends on early detection. We developed and externally validated a model using routine, readily available clinical...

Personalized surveillance in giant congenital melanocytic nevus, including the role of AI, histopathology and MC1R genotyping: A case report.

Giant congenital melanocytic nevi (GCMN) are rare pigmented skin lesions present at birth that carry an increased risk of malignant melanoma and neuro...

Single-Cell Morphometrics From Hematoxylin and Eosin-Stained Images Reveals Subtype-Specific Features in Chronic Lymphocytic Leukemia.

Chronic lymphocytic leukemia (CLL) is a highly heterogeneous B-cell malignancy, spanning a spectrum from indolent conventional forms (C-CLL) to Richte...

Performance validation of a closed loop fully automated AI model for lung nodule stratification in screening cases.

BACKGROUND: Several limitations hinder the effectiveness of human-based lung cancer screening (LCS): high false-positive rates leading to unnecessary ...

UniCAS: A foundation model for cervical cytology screening.

Cervical abnormality screening is pivotal for prevention and treatment. However, the substantial size of whole slide images (WSIs) makes examination l...

[Evaluation of an interpretable 12-lead ECG automatic diagnosis model based on deep feature fusion].

OBJECTIVES: To enhance the accuracy and reliability of 12-lead electrocardiogram (ECG) automatic diagnosis. METHODS: Herein we propose a 12-lead ECG a...

Validation of histopathology-based deep learning algorithms for detection of actionable non-small cell lung cancer biomarkers.

Non-small cell lung cancer (NSCLC) patient management relies on molecular analysis to determine eligibility for targeted therapy. Furthermore, neoadju...

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics.

Defects in layered transition metal dichalcogenides play a crucial role in the development of high-energy-density and high-safety electrochemical devi...

S3RL: Enhancing Spatial Single-Cell Transcriptomics With Separable Representation Learning.

Spatial transcriptomics enables in situ mapping of gene expression, offering insights into tissue organization and cell-cell interactions. However, it...

Novel Aggressive Subtype of Multiple System Atrophy Identified by Unsupervised Machine Learning.

OBJECTIVES: Multiple system atrophy (MSA) is classified into parkinsonian (MSA-P) and cerebellar (MSA-C) phenotypes based on predominant motor feature...

Iron Oxide-Based Surface-Enhanced Raman Spectroscopy Bioprobes for Detecting Tumor Cells in Serous Effusion.

Serous effusions, including pleural effusion and ascites, commonly occur in advanced cancers like lung and ovarian carcinomas. Detecting tumor cells i...

Noise in the diagnosis of epilepsy by experts.

OBJECTIVE: To measure the relative levels of signal and noise in expert diagnosis of epilepsy. METHODS: Twenty multinational epileptologists independe...

The Diagnosis and Treatment Technology of Port-Wine Stain, and the Prospect of Future Treatment.

Port-wine stain (PWS) is a congenital capillary malformation with a 0.3-0.5% prevalence. This article reviews key techniques and advancements in the d...

Novel Artificial Intelligence Chest X-ray Diagnostics: A Quality Assessment of Their Agreement with Human Doctors in Clinical Routine.

The rising demand for radiology services calls for innovative solutions to sustain diagnostic quality and efficiency. This study evaluated the diagnos...

Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood...

Deep learning-based no-reference image quality assessment framework for Cryptosporidium spp. and Giardia spp.

Image Quality Assessment (IQA) plays a critical role in image-based decision-making systems, especially in domains requiring high diagnostic precision...

Evaluation of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Incidental Pulmonary Nodules: The CREATE Study.

OBJECTIVE: To evaluate the effectiveness of the artificial intelligence-based qXR lung nodule malignancy score (qXR-LNMS) in detecting high-risk incid...

Validation of uPath HER2 dual-colour dual in-situ hybridisation image analysis tool for HER2/neu testing in breast cancer.

AIMS: HER2/neu gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical prognostic and predictive marker. HER2-targeted the...