Pathology

Machine and deep learning models for accurate detection of ischemia and scar with myocardial blood flow positron emission tomography imaging.

BACKGROUND: Quantification of myocardial blood flow (MBF) is used for the noninvasive diagnosis of patients with coronary artery disease (CAD). This study compared traditional statistics, machine learning, and deep learning techniques in their ability to diagnose disease using only the rest and stress MBF values.

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas.

Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment within 24-48 h from the onset of the symptoms. The increasing number of imported malaria cases as well as the risk of the reintroduction of autochthonous cases encouraged laboratories in non-endemic countries to adopt diagnostic methods/algorithms. ...

Leukocyte differential based on an imaging and impedance flow cytometry of microfluidics coupled with deep neural networks.

The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitati...

Phytochemical and biological studies of aerial parts ethanol extract supported by molecular docking study.

has traditionally been used as a poultice to alleviate local inflammation and painful diseases. This study aimed to evaluate the anti-inflammatory, w...

Biomarkers and molecular endotypes of sarcoidosis: lessons from omics and non-omics studies.

Sarcoidosis is a chronic granulomatous disorder characterized by unknown etiology, undetermined mechanisms, and non-specific therapies except TNF bloc...

Construction and evaluation of endometriosis diagnostic prediction model and immune infiltration based on efferocytosis-related genes.

Endometriosis (EM) is a long-lasting inflammatory disease that is difficult to treat and prevent. Existing research indicates the significance of imm...

From Staining Techniques to Artificial Intelligence: A Review of Colorectal Polyps Characterization.

This review article provides a comprehensive overview of the evolving techniques in image-enhanced endoscopy (IEE) for the characterization of colorec...

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and ag...

MAPS: pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native conte...

Diagnostic value of artificial intelligence based on computed tomography (CT) density in benign and malignant pulmonary nodules: a retrospective investigation.

OBJECTIVE: To evaluate the diagnostic value of artificial intelligence (AI) in the detection and management of benign and malignant pulmonary nodules ...

Exploring Deep Learning for Estimating the Isoeffective Dose of FLASH Irradiation From Mouse Intestinal Histological Images.

PURPOSE: Ultrahigh-dose-rate (FLASH) irradiation has been reported to reduce normal tissue damage compared with conventional dose rate (CONV) irradiat...

Integrative analysis of RNA expression data unveils distinct cancer types through machine learning techniques.

Cancer is a highly complex and heterogeneous disease. Traditional methods of cancer classification based on histopathology have limitations in guiding...

Improved bioimpedance spectroscopy tissue classification through data augmentation from generative adversarial networks.

Bioimpedance spectroscopy is a tissue classification technique with many clinical applications. Similarly to other data-driven methods, it requires la...

Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.

We propose DiRL, a Diversity-inducing Representation Learning technique for histopathology imaging. Self-supervised learning (SSL) techniques, such as...

Microscopic urinary particle detection by different YOLOv5 models with evolutionary genetic algorithm based hyperparameter optimization.

The diagnosis of kidney disease often involves analysing urine sediment particles. Traditionally, urinalysis was performed manually by collecting urin...

Leveraging Machine Learning for Size and Shape Analysis of Nanoparticles: A Shortcut to Electron Microscopy.

Characterizing nanoparticles (NPs) is crucial in nanoscience due to the direct influence of their physiochemical properties on their behavior. Various...

Deep Learning Image Recognition-Assisted Atomic Force Microscopy for Single-Cell Efficient Mechanics in Co-culture Environments.

Atomic force microscopy (AFM)-based force spectroscopy assay has become an important method for characterizing the mechanical properties of single liv...

Classification of Multiple H&E Images via an Ensemble Computational Scheme.

In this work, a computational scheme is proposed to identify the main combinations of handcrafted descriptors and deep-learned features capable of cla...

Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies.

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum...

Application of Artificial Intelligence at All Stages of Bone Tissue Engineering.

The development of artificial intelligence (AI) has revolutionized medical care in recent years and plays a vital role in a number of areas, such as d...