Pathology

Radiomics-based ultrasOund Model for differentiating Uterine Sarcomas from leiomyomas (ROMUS): a retrospective pilot Multicenter Italian Trials in Ovarian Cancer (MITO) study.

OBJECTIVE: To develop machine-learning models that incorporate clinical information and radiomics features extracted from ultrasound images to distinguish uterine sarcomas from leiomyomas. METHODS: This retrospective, multicenter, pilot case-control study included 200 patients (100 with a uterine sarcoma and 100 with a usual-type leiomyoma, i.e. including no benign leiomyoma variants) who underwen...

Fragmentomic liquid biopsy enables early breast cancer detection, molecular subtyping and lymph node assessment.

Breast cancer remains a leading global health concern in women, while screening is still limited by imaging accessibility and reduced sensitivity in dense breasts. Here we conduct a multicenter case-control study including 503 breast cancer patients and 289 benign controls to develop TuFEst, a machine learning model based on genome-wide cell-free DNA fragmentomic features. TuFEst achieves high sen...

Percutaneous nephrostomy guidance by a convolutional-neural-network-based optical coherence tomography endoscope.

Percutaneous nephrostomy is widely used in kidney access surgeries. Despite its prevalence in urological interventions, it presents two operational ch...

A confidence-based, artificial intelligence pathology model for diagnosis of intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICCA) is a rare but highly lethal adenocarcinoma arising within the hepatic parenchyma. Diagnosis present...

Deep Learning-Derived Body Composition Analysis Predicts Long-Term Mortality After Transcatheter Aortic Valve Replacement.

OBJECTIVE: To examine the association between body composition metrics derived from preprocedural computed tomography (CT) angiography and all-cause m...

Artificial Intelligence-based Gram Stain Classification: Accuracy and Clinical Utility in Positive Blood Cultures.

INTRODUCTION: With the rapid advancement of artificial intelligence (AI) technology, AI has been applied to the detection of pathogens that cause infe...

Unraveling the connection between PFOA and bladder cancer: A study integrating network toxicology, molecular docking, and experimental validation.

PFOA, an environmental pollutant linked to bladder cancer, has unclear molecular mechanisms. Integrating transcriptomic data with network toxicology a...

Advances in the application of photodynamic diagnosis in Skin Tumors.

Photodynamic Diagnosis (PDD) is a non-invasive imaging technique. It relies on a photosensitizer that, when activated by a specific light source, caus...

CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification.

Effective diagnosis and treatment of lung adenocarcinoma depends on accurate typing, subtyping, and grading. Herein, we present the CLWD dataset, a va...

Deep learning-based histopathological classification and subclassification of benign and malignant salivary gland tumors.

Application of treatment response assessment maps (TRAMs), based on delayed-contrast MRI for radiomic characterization of breast lesions.

Dynamic contrast-enhanced (DCE) breast MRI is a highly sensitive modality for detecting breast cancer, but its limited specificity often leads to fals...

Artificial intelligence-based pathological model for pan-cancer lymph node metastasis detection: a multicentre diagnostic study with retrospective and prospective validation.

BACKGROUND: Accurate detection of lymph node metastasis is crucial for precise tumour staging and treatment planning. Conventional pathological examin...

Differentiation of Benign and Malignant Cervical Lymph Nodes Using a Multi-Modal Ultrasound-Based Machine Learning Model with SHAP Interpretability.

OBJECTIVES: To evaluate the diagnostic value of a machine learning (ML) model based on multi-modal ultrasound features in differentiating benign from ...

A framework for identifying the polyploid complex in Rorippa (Brassicaceae): combining trait evolution, herbarium records, and machine learning.

BACKGROUND AND AIMS: Species identification in polyploid plants remains challenging due to morphological continuity and genomic redundancy. Such taxon...

Noninvasive Blood-Based Detection of Endometriosis Can Improve Standard-of-Care by Facilitating Early Diagnosis and Clinical Management Among Symptomatic Women.

STUDY OBJECTIVE: To develop and validate a non-invasive, blood-based diagnostic assay for endometriosis that performs accurately across menstrual cycl...

An advanced diagnostic framework for discriminating lung cancer tissue subtypes via the synergy of fourier transform infrared spectroscopy and random forest.

Accurate subtyping of lung cancer is essential for improving patient prognosis and enabling personalized treatment. However, current clinical techniqu...

Decomposition based curriculum-style self-training for source-free universal domain adaptation in computational pathology.

Computational pathology models serve as crucial tools for clinical tasks such as tissue typing, alleviating the burden of manual screening of whole sl...

Biosensor-based diagnosis for infectious diseases: Nano-enabled revolution.

Infectious diseases (IDs) pose a significant global health threat, exacerbated by the rise of multidrug-resistant (MDR) and antimicrobial-resistant (A...

Reflectance confocal microscopy in the management of lentigo maligna and lentigo maligna melanoma: a systematic review.

BACKGROUND: Lentigo maligna (LM) and lentigo maligna melanoma (LMM) are difficult to manage because of their subclinical extension and ill-defined mar...

Risk factors for postoperative recurrence of sinonasal inverted papilloma: a retrospective analysis of 171 cases.

BACKGROUND: Sinonasal inverted papilloma(SNIP) is a benign tumor with a potential of malignant transformation but has a certain recurrence. OBJECTIVES...