Pathology

Multi-omics and AI-guided discovery and validation of sisomicin as a COPA-targeting agent for pathological scar inhibition.

BACKGROUND: Pathological scars, including hypertrophic scars and keloids, are fibrotic skin disorders marked by excessive collagen deposition and persistent inflammation, yet effective treatments remain limited. METHODS: We integrated single-cell RNA sequencing, bulk transcriptomic datasets, and artificial intelligence (AI)-driven machine learning and deep learning to identify molecular drivers of...

Digital Enabled Diagnosis System for Mammogram Images Classification Using Machine Learning.

Breast tumor is the most commonly detected tumors and remain one of the leading causes of cancer-related mortality among women worldwide. Although mammography is widely adopted for early breast cancer screening, existing diagnostic systems are often time-consuming and highly dependent on expert radiologists. Moreover, mammogram images frequently suffer from noise and low contrast, which can result...

Computerized diagnosis of brain tumor using graph based CNN classification.

Magnetic resonance imaging (MRI) is essential in the accurate diagnosis of brain tumors so that sound treatment planning can be done, however, clinica...

Integrative assessment of sulfoxaflor effects on gene expression, reproduction, and behavior in the bumblebee Bombus impatiens.

Social insect pollinators, such as bumblebees, face increasing threats from environmental agrochemicals; yet the sublethal effects of these compounds ...

Digital SERS Nanoprobe Immunoassay With Single-Particle Sensing Resolution for Detection of Pancreatic Cancer Biomarkers From Clinical Blood Samples.

Surface-enhanced Raman scattering (SERS) nanoprobe-based immunoassay is an emerging liquid biopsy modality for the detection of blood biomarkers. Howe...

A practical framework for super-resolution of mass spectrometry images via adaptation of deep learning models.

Achieving high spatial resolution is critical for revealing tissue-specific metabolite distributions in mass spectrometry imaging (MSI), yet practical...

Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy.

Purpose To develop an explainable radio-pathomic graph deep-learning (RPGDL) system for multiscale spatial-contextual modeling of intratumoral heterog...

Development of an Integrated Deep Learning Approach for Detecting Fetal Brain Abnormalities in Routine Second Trimester Ultrasound Scan: A Multicenter Study.

Purpose To develop and validate an anatomy-aware, two-stage, end-to-end deep learning (DL) pipeline for fetal brain abnormality automated detection on...

Integrated multi-omics and experimental validation for identifying novel biomarkers of acute myocardial infarction.

Acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality, and early diagnosis and personalized therapy are constrained by ...

Machine Learning-Assisted High-Temperature Nonequilibrium Kinetics of Air Components: From Microscale to Macroscale.

The growing demand for reproducing state-to-state (StS) level accuracy in modeling the nonequilibrium kinetics of air components at temperatures above...

MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network.

Skin cancer has become a global public health issue. Dermoscopy is a routine diagnostic method; however, to improve accuracy, it is often combined wit...

Identification of biomarkers for non-invasive diagnosis and risk stratification in prostate cancer using NMR-based metabolomics and machine learning.

The non-invasive diagnosis and risk stratification of prostate cancer (PCa) remain clinically challenging due to the limited specificity of prostate-s...

Segment anything small for ultrasound: Enhancing segmentation with non-generative augmentation.

Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability in imag...

Finding Holes: Pathologist-Level Performance Using AI for Cribriform Morphology Detection in Prostate Cancer.

BACKGROUND: Cribriform morphology in prostate cancer is a histological feature that indicates poor prognosis and contraindicates active surveillance. ...

Interpretative diagnostic model for neuroblastoma metastases using bone marrow cytology.

EFSUMB Guidelines on Multiparametric Ultrasound Thyroid Nodule Evaluation: PART I.

Thyroid nodules are common incidental findings, but only a small proportion of cases are malignant (4-6.5%) or symptomatic. Numerous follow-up examina...

EFSUMB Guidelines on Multiparametric Ultrasound Thyroid Nodule Evaluation: PART II.

Thyroid nodules are common incidental findings but only a small proportion of cases are malignant (4-6.5%) or symptomatic. Numerous follow-up examinat...

Utilizing Deep Learning-based Computed Tomography Fractional Flow Reserve on Coronary Artery Disease Diagnosis and Treatment: 1-year Clinical Application From a Chinese Major Hospital.

PURPOSE: Machine learning-based coronary computed tomography fractional flow reserve (CT-FFR) holds great potential for assessing coronary ischemic st...

Beyond Weight: Systems Biology and Precision Medicine Redefine Obesity as a Multidimensional Disease.

BACKGROUND: Traditional weight-centered models do not fully capture the biological complexity of obesity. Systems biology offers a new framework by in...

State-of-the-art of surface-enhanced Raman spectroscopy for pathogenic bacterial identification.

Rapid and accurate identification of pathogenic bacteria is essential for safeguarding public health. However, existing approaches, including conventi...