Pathology

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 arbitrarily thick biological specimens. However, in its initial embodiment, qOBM requires multiple captures for phase recovery, which reduces imaging speed and increases system complexity. In this work, we present a novel advancement in qOBM: single-capture ...

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 molecular testing. Here we show, through statistical analysis across multiple cancer types, datasets and modelling approaches, that the datasets used to train these models contain strong dependencies between biomarkers and clinicopathological features, wh...

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...

Impact of tissue staining and scanner variation on the performance of pathology foundation models: a study of sarcomas and their mimics.

Histopathological analysis is considered the gold standard for the diagnosis and prognostication of cancer. Recent advances in AI, driven by large-sca...

Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort.

Sudden arrhythmic death syndrome (SADS) is a major cause of sudden cardiac death in young individuals, characterized by structurally normal hearts and...

Feasibility of an Augmented Reality Artificial Intelligence Tool for Real-Time Assessment of Thyroid Fine-Needle Aspiration Adequacy.

PURPOSE: To evaluate the feasibility of developing an artificial intelligence application for real-time specimen adequacy assessment during ultrasound...

Metabolic liver imaging: What you need to know.

Metabolic liver diseases represent a growing global health concern with significant diagnostic and prognostic implications. Imaging offers non-invasiv...

Single-nucleus multi-omics dissection of dysregulated trophoblast development and disrupted immune microenvironment in complete hydatidiform moles.

Hydatidiform mole (HM) is driven by aberrant trophoblast proliferation, disrupting embryonic development and leading to pregnancy loss with increased ...

Puerarin mitigates tumor necrosis factor-nuclear factor-κB axis-driven macrophage inflammation and atherogenesis: Integrative network pharmacology and experimental validation.

BACKGROUND: Atherosclerosis (AS) is a chronic inflammatory disease that constitutes the primary pathological basis of cardiovascular disorders. Althou...

Particle-Based Detection of Surface Chemistry via Optical Microscopy-Integrating Microfluidics, Light-Induced Activity of Colloids and Data Science.

We present particle-resolved methods for determining the porosity and surface area of microparticles, based on single-particle trajectory analysis con...

Machine Learning-Informed Nano Co-Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue.

Nanoparticle-based drug delivery faces persistent challenges, including complex fabrication processes and limited lesional accumulation. Here we intro...