Pathology

Multiparametric AI-based perfusion analysis outperforms Tmax thresholding for critically hypoperfused tissue estimation in acute ischemic stroke undergoing admission MRI.

OBJECTIVE: Perfusion imaging is used to estimate critically hypoperfused tissue in acute ischemic stroke (AIS), commonly using threshold-based methods. This study compared an artificial intelligence (AI)-driven multiparametric approach with conventional thresholding for estimating ischemic core and hypoperfused tissue volumes. MATERIALS AND METHODS: We analyzed 186 AIS patients from the HIBISCUS-S...

How good are artificial intelligence tools at identifying benign skin lesions? A systematic review and meta-analysis of the specificity of artificial intelligence tools in diagnosing suspicious skin lesions.

BACKGROUND: Artificial intelligence (AI) is a transformative diagnostic tool in dermatology. As the prevalence of skin cancer rises and pressure on health services increases, there is an increasing demand for efficient diagnostic tools. Therefore, it is highly relevant to evaluate the diagnostic abilities of AI tools with a focus on not just the sensitivity, but also the specificity, to reduce unn...

Incorporating artificial intelligence into morphological diagnosis of acute leukemias: Current landscape, challenges and prospects (Review).

Acute leukemias (ALs) are a diverse group of hematological malignancies characterized by the abnormal proliferation of immature cells. Microscopic obs...

Macrophage polarization as a therapeutic target in lung diseases: From pathogenesis to precision intervention.

Macrophages serve as core effector cells of the innate immune system, exerting dual regulatory roles in pulmonary homeostasis maintenance and disease ...

Combined multi-omics and multi-spectral profiling of plasma extracellular vesicles reveals liquid biopsy biomarkers for glioma diagnosis.

Plasma small extracellular vesicles (sEVs) are a promising liquid biopsy tool. This study aims to delineate and validate a multimodal plasma sEV bioma...

Reconstruction of emergence profile using a digital mirroring technique in a custom biological definitive abutment and interim restoration in immediate implant placement in esthetic area: A clinical report with 4-year follow-up.

Immediate implant placement and interim restoration in the anterior maxilla remains challenging because of the high esthetic demands and the risk of s...

Application of an open-source AI tool for quantitative quality control in whole slide images of prostate needle core biopsies - a retrospective study.

The quality of Whole Slide Images (WSI) is a determining factor for proper diagnosis and prognosis, and for enhanced performance of Digital and Comput...

Integrating Sperm Microscopy, Environmental Exposures, and Lifestyle Factors for Male Fertility Analysis: Protocol for the Nippon Semen and Environmental Exposure Database (N-SEED) Cross-Sectional Study.

BACKGROUND: Conventional semen analysis does not fully capture male reproductive potential. The sperm DNA fragmentation index (DFI) may detect latent ...

The SPECT/CT radiomics-based classification of skeletal metastases and benign bone lesions.

Hybrid Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) improves lesion localization and diagnostic accuracy in detecting ske...

A pyroptosis-related gene signature for the diagnosis of acute pancreatitis.

Acute pancreatitis (AP) is a severe inflammatory disorder in which pyroptosis-a pro-inflammatory form of programmed cell death-may contribute to patho...

Transformer-based multi-agent traffic simulation for autonomous vehicle testing in shared urban road segments.

Microscopic traffic simulation plays a crucial role in the development and testing of autonomous driving systems. However, accurately reproducing traf...

Large Language Models for the Differentiation of Benign and Malignant Liver Nodules based on Multimodal Prompts in Liver US Cases.

OBJECTIVE: Large language models (LLMs) that can process both images and text are increasingly being used in radiology. This study aimed to evaluate t...

Machine learning and deep learning models for predicting colorectal cancer metastases: A comprehensive review.

Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, largely due to the development of distant metastases, which is assoc...

Changes in computed tomography derived muscle and pulmonary tissue in patients hospitalized for COVID-19: a 12-month follow-up study.

BACKGROUND: Prolonged muscle loss and persistent pulmonary radiological manifestations have been observed among previously hospitalized COVID-19 patie...

Non-invasive diagnosis strategy integrating PSMA PET/CT and mpMRI for patients with suspected prostate cancer: a multi-center study.

BACKGROUND: Multiparametric MRI (mpMRI) and ^68 Ga-PSMA PET/CT are widely used for prostate cancer (PCa) diagnosis but remain limited by false positiv...

Identification and selection of the best artificial intelligence methods developed for detection and diagnosis of breast cancer.

BACKGROUND: Comprehensive identification and prioritization of developed artificial intelligence methods for the detection and diagnosis of breast can...

What is diagnosis in the age of artificial intelligence.

The integration of artificial intelligence into clinical practice demands fundamental reconsideration of how we conceptualize diagnosis. Clinical and ...

Deep learning and cryogenic electron microscopy modeling for gene editing dynamics.

Advances in cryogenic electron microscopy (cryo-EM) data modeling and deep learning are reshaping our ability to interrogate and engineer genome-editi...

Screening of molecular signatures from microRNA and mRNA expression profiling related to the efficacy of the antidepressant duloxetine and analysis of their regulatory relationship.

Previous clinical studies have reported that not all depressed patients respond to antidepressants. Therefore, finding potential predictive molecular ...

Noninvasive Prediction of Bone Metastasis-Free Survival in Lung Adenocarcinoma Using Interpretable CT-based Deep Learning Model.

RATIONALE AND OBJECTIVES: Preoperatively identifying patients at high risk of bone metastasis (BM) remains challenging in resectable lung adenocarcino...