Pathology

AI-driven multiscale virtual plant cell modeling: from molecular mechanisms to tissue functions.

AI-driven multiscale virtual plant cell modeling represents a paradigm shift in plant systems biology, enabling predictive simulation from molecular mechanisms to tissue functions and accelerating the engineering of climate-resilient crops. AI-driven multiscale virtual plant cell modeling is emerging as a pivotal paradigm for deciphering complex biological processes in plants. By integrating dynam...

Inferring crowd crush accidents in typical high-density pedestrian movement zones via the vision-trajectory fusion neural network.

Pedestrian walking constitutes an indispensable mode of daily travel, yet recurrent high-density crowd gatherings in relevant facilities, e.g., holiday surges at railway stations, are widely recognized as high risk factors that can precipitate crowd crush accidents. To facilitate effective prevention, this study provides a foundational step by enabling precise inference of spatio-temporal crowd ev...

Interpreting chemical crosslinks: Score-based approaches and deep neural networks.

Chemical cross-linking coupled with mass spectrometry (XL-MS) has become a powerful tool for probing residue-level proximities within macromolecular a...

Redefining Cytotechnologist Practice in Sweden: National Survey on Workload, Expanded Roles, and Future Competency Needs.

INTRODUCTION: Cytotechnologists have long been central to cervical cancer screening, although their education and job responsibilities differ markedly...

Topology-aware Diffusion Schrödinger Bridge for Unpaired H&E-to-IHC Stain Translation.

Unpaired H&E-to-IHC Stain Translation aims to generate immunohistochemistry (IHC) staining from Hematoxylin and Eosin (H&E) staining. It offers cleare...

Epithelial Na+/K+ Imbalance and Impaired Na+/K+-ATPase Activity as Surface Markers of Airway Remodelling in Obstructive Sleep Apnea.

Airway remodelling in obstructive sleep apnea encompasses diverse histopathological and neuromuscular alterations, yet surface-level epithelial change...

Image-to-molecule benchmarking dataset with fractal pattern and hierarchical morphology recognition.

The unique phenomenon of high morphological diversity of quaternary phosphonium salts (QPSs) has been observed via electron and optical microscopy. Th...

Benchmarking multiple instance learning architectures from patches to pathology for prostate cancer detection and grading using attention-based weak supervision.

Histopathological evaluation is necessary for the diagnosis and grading of prostate cancer, which is still one of the most common cancers in men globa...

Single capture quantitative oblique back-illumination microscopy.

Quantitative oblique back-illumination microscopy (qOBM) has emerged as a powerful technique for label-free, 3D quantitative phase imaging of arbitrar...

Confounding factors and biases abound when predicting molecular biomarkers from histological images.

Deep learning models that infer clinically relevant biomarker status from tissue images are being explored as rapid and low-cost alternatives to molec...

From imaging to omics: deep learning is bridging MRI and liquid biopsy in bone tumor diagnosis.

Bone tumors such as osteosarcoma and Ewing sarcoma remain among the most challenging cancers to diagnose and monitor because of their biological heter...

ORANGE: a machine learning approach for modeling tissue-specific aging from transcriptomic data.

Despite aging being a fundamental biological process that profoundly influences health and disease, the interplay between tissue-specific aging and mo...

Meta-Learning With Unlabeled Query Updating and Consistency Learning for Few-Shot OCT Image Classification.

OBJECTIVE: Deep neural networks are widely used in the field of optical coherence tomography (OCT) to screen some common retinal diseases. However, fo...

Renal interstitial inflammation predicts IgA nephropathy progression via multiple machine learning models.

BACKGROUND: Renal interstitial inflammation (RII) is a frequent pathological feature in IgA nephropathy (IgAN), but its prognostic value remains uncer...

Artificial Intelligence in Coronary Computed Tomography: Current Applications, Future Potentials, and Real-world Challenges.

Artificial intelligence (AI) is rapidly transforming cardiac computed tomography (CT) imaging by enhancing image acquisition, reconstruction, and anal...

CryoJAX: a cryo-electron microscopy image-simulation library in JAX.

While cryo-electron microscopy (cryo-EM) has come to prominence in the last decade due to its ability to resolve biomolecular complexes at atomic reso...

Leveraging artificial intelligence to decipher gynecologic cytopathology reports: Insights from an exploratory study for possible use in patient portals.

BACKGROUND: The 21st Century Cures Act allows patients to have immediate access to their medical records. However, it is documented that health litera...

Evaluating Performance of a Deep Learning-based Artificial Intelligence Model for Ovarian Tumor Classification Using a Multicenter CT Dataset.

Purpose To develop a deep learning-based, computer-aided diagnosis (CADx) model for preoperative classification of ovarian tumors (OTs) on CT scans an...

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements.

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and res...

A Self-Supervised Foundation Model Based on Three-Dimensional Chest CT Scans for Lung Cancer Diagnosis and Prognosis Prediction.

Purpose To develop a self-supervised chest CT foundation model and evaluate its performance in lung cancer clinical tasks. Materials and Methods In th...