Pathology

Prospective clinical validation of a novel artificial intelligence system for real-time detection of solid pancreatic masses during endoscopic ultrasonography.

Endoscopic ultrasonography (EUS) is the most sensitive modality for accurately establishing a tissue diagnosis in patients with solid pancreatic masses. However, small lesions can be challenging to detect, particularly for less experienced endosonographers. Therefore, outcomes of EUS are operator dependent. We validated the performance of novel artificial intelligence (AI)-enhanced EUS for detecti...

Decoding the gut microbiota metabolite-matrix metalloproteinase-3 axis in breast cancer: a multi-omics and network pharmacology study.

Breast cancer is a malignant tumor originating from the breast epithelium, and emerging evidence suggests that the gut microbiota influences its development, progression, and treatment, although its role remains underexplored. In this study, we employed an integrative multi-omics framework that combined network pharmacology, machine learning, SHapley Additive exPlanations (SHAP), and single-cell R...

Unconventional bioprinting modalities for advanced tissue biofabrication.

Bioprinting has been widely used to fabricate three-dimensional constructs for various applications. However, conventional bioprinting modalities face...

Machine learning models for predicting recurrence and malignant transformation of oral leukoplakia.

OBJECTIVE: This study aimed to evaluate machine learning models for predicting the recurrence and malignant transformation of oral leukoplakia (OL). M...

Multimodal deep learning method based on multiple spectra for lung cancer early diagnosis.

Lung cancer remains one of the most lethal malignancies worldwide, and the early and accurate diagnostic is critical. Traditional diagnostic technique...

Evaluation of the Detectability of Oral Potentially Malignant Diseases with a Deep Learning Approach: A Retrospective Pilot Study.

Oral potentially malignant diseases (OPMD) may arise during the malignant transformation of the oral mucosa, with cellular changes in these lesions in...

Application of Convolutional Neural Network Image Analysis and Machine Learning to Basic Blood Tests for Intelligent Diagnostic Assistance.

BACKGROUND AND OBJECTIVES: We developed an automated morphological image recognition deep learning system (image recognition DLS) of peripheral blood ...

Early prediction of orthodontic gingival enlargement using S100A4: a biomarker-based risk stratification model.

Orthodontic-induced gingival enlargement (OIGE) affects approximately 15-30% of patients undergoing orthodontic treatment and remains largely unpredic...

From early-life fluoxetine exposure to lifelong, sex-specific behavioral changes: decoding the dynamics of sensitive periods.

Early-life experiences shape neural networks, with heightened plasticity during the so-called "sensitive periods" (SP). SP are regulated by the matura...

Integration of machine learning and SERS technology for precise classification and diagnosis of colon cancer from plasma samples.

Surface-Enhanced Raman Spectroscopy (SERS) combined with machine learning offers a transformative label-free approach for colorectal cancer detection,...

Leveraging Machine Learning for Rapid and Accurate Diagnosis of Acute Leukemia.

CONTEXT: Early detection of acute leukemia (AL) is crucial for timely intervention and improved outcomes. Machine learning (ML) models provide a promi...

A deep learning-clinical nomogram hybrid for predicting sentinel lymph node metastasis in melanoma.

BACKGROUND: Melanoma is a life-threatening skin malignancy, with sentinel lymph node metastasis (SLNM) serving as a critical prognostic factor. While ...

MRI-based deep learning radiomics in predicting histological differentiation of oropharyngeal cancer: a multicenter cohort study.

BACKGROUND: The primary aim of this research was to create and rigorously assess a deep learning radiomics (DLR) framework utilizing magnetic resonanc...

Residual disease in NPM1-mutated acute myeloid leukemia.

Acute myeloid leukemia (AML) represents a genetically heterogeneous malignancy, with mutations in the nucleophosmin-1 (NPM1) gene identified as the mo...

Comparison of the diagnostic performance of the artificial intelligence-based TIRADS algorithm with established classification systems for thyroid nodules.

PURPOSE: This study aimed to evaluate and compare the diagnostic performance of various Thyroid Imaging Reporting and Data Systems (TIRADS), with a pa...

Application of artificial intelligence in oral potentially malignant disorders: current opinions and future barriers.

Oral potentially malignant disorders (OPMDs) refer to oral mucosal disorders with an increased risk of malignancy, primarily oral squamous cell carcin...

Artificial Intelligence Diagnosis of Ocular Motility Disorders From Clinical Videos.

BACKGROUND: Multimodal artificial intelligence (AI) models have recently expanded into video analysis. In ophthalmology, one exploratory application i...

Machine learning models to predict postoperative incontinence after endoscopic enucleation of the prostate for benign prostatic hyperplasia: An EAU-Endourology study.

BACKGROUND: Machine learning (ML) and artificial intelligence (AI) have demonstrated powerful functionality in the healthcare setting thus far. We aim...

Deep learning-based quantitative assessment of renal chronicity indices in lupus nephritis.

Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However, assessment by...

Diagnostic Accuracy of a Large Language Model (ChatGPT-4) for Patients Admitted to a Community Hospital Medical Intensive Care Unit: A Retrospective Case Study.

BackgroundThe future of artificial intelligence in medicine includes the use of machine learning and large language models to improve diagnostic accur...