Pathology

Artificial intelligence predicts multiclass molecular signatures and subtypes directly from breast cancer histology: a multicenter retrospective study.

Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a dee...

[Research progress of effect mechanism of acupotomy for knee osteoarthritis].

Acupotomy therapy demonstrates the definite clinical efficacy on knee osteoarthritis (KOA). After re...

Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis.

The worldwide prevalence of glaucoma makes it a major reason for blindness thus proper early diagnos...

Digital quantification of Ki67 and PRAME in challenging melanocytic lesions - A novel diagnostic tool.

The interpretation of immunohistochemical markers in melanocytic lesions possesses difficulties due ...

Comprehensive testing of large language models for extraction of structured data in pathology.

BACKGROUND: Pathology departments generate large volumes of unstructured data as free-text diagnosti...

Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.

Pancreatic cancer (PC) is a fatal disease with an extremely low 5-year survival rate, mainly because...

Computer-assisted diagnosis to improve diagnostic pathology: A review.

With an increasing demand for accuracy and efficiency in diagnostic pathology, computer-assisted dia...

Multimodal contrastive learning for enhanced explainability in pediatric brain tumor molecular diagnosis.

Despite the promising performance of convolutional neural networks (CNNs) in brain tumor diagnosis f...

[Artificial intelligence-based fusion prostate biopsy].

Ultrasound-based deep learning to differentiate salivary gland tumors.

OBJECTIVE: Accurate preoperative diagnosis is essential for selecting appropriate surgical intervent...

Deep structural brain imaging via computational three-photon microscopy.

SIGNIFICANCE: High-resolution optical imaging at significant depths is challenging due to scattering...

Advancements in Circulating Tumor Cell Detection for Early Cancer Diagnosis: An Integration of Machine Learning Algorithms with Microfluidic Technologies.

Circulating tumor cells (CTCs) are vital indicators of metastasis and provide a non-invasive method ...

A deep-learning algorithm (AIFORIA) for classification of hematopoietic cells in bone marrow aspirate smears based on nine cell classes-a feasible approach for routine screening?

Bone marrow cytology plays a key role for the diagnosis and classification of hematological disease ...

ULST: U-shaped LeWin Spectral Transformer for virtual staining of pathological sections.

At present, pathological section staining faces several challenges, including complex sample prepara...

Exploring the Incremental Value of Aorta Enhancement Normalization Method in Evaluating Renal Cell Carcinoma Histological Subtypes: A Multi-center Large Cohort Study.

RATIONALE AND OBJECTIVES: The classification of renal cell carcinoma (RCC) histological subtypes pla...

Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning.

BACKGROUND: Distinguishing between benign and malignant testicular lesions on clinical magnetic reso...

Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries.

The most prevalent malignancy among women is breast cancer; hence, treatment approaches are needed i...

Automated Radiology Report Labeling in Chest X-Ray Pathologies: Development and Evaluation of a Large Language Model Framework.

BACKGROUND: Labeling unstructured radiology reports is crucial for creating structured datasets that...

The growing field of liquid biopsy and its Snowball effect on reshaping cancer management.

Liquid biopsy (LB) has emerged as a transformative tool in oncology, providing a minimally invasive ...

Imaging and spatially resolved mass spectrometry applications in nephrology.

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying ...

Automated assessment of skin histological tissue structures by artificial intelligence in cutaneous melanoma.

BACKGROUND: Prognostic histopathological features such as mitosis in melanoma are excluded from the ...