Pathology

Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.

BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer ...

A radiomics-based interpretable model integrating delayed-phase CT and clinical features for predicting the pathological grade of appendiceal pseudomyxoma peritonei.

OBJECTIVE: This study aimed to develop an interpretable machine learning model integrating delayed-p...

Machine learning-based MRI imaging for prostate cancer diagnosis: systematic review and meta-analysis.

OBJECTIVE: This study aims to evaluate the diagnostic value of machine learning-based MRI imaging in...

Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection.

Breast cancer is a relatively common carcinoma among women worldwide and remains a considerable publ...

Wavelet-Attention deep model for pediatric ADHD diagnosis via EEG.

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in childr...

Artificial intelligence-driven pathomics in hepatocellular carcinoma: current developments, challenges and perspectives.

Hepatocellular carcinoma (HCC) is a highly malignant tumor with elevated incidence and mortality rat...

Advancements in lung cancer: molecular insights, innovative therapies, and future prospects.

Still among the most common and deadly cancers worldwide, lung cancer causes major morbidity and dea...

Machine Learning-Assisted Tissue-Residue-Based Risk Assessment for Protecting Threatened and Endangered Fishes in the Yangtze River Basin.

Assessing pollutant risks to threatened and endangered (T&E) species is crucial for their conservati...

Improved risk assessment in parvovirus B19-positive patients with heart failure by multiparametric analysis of endomyocardial biopsy using machine learning methods.

AIMS: The analysis of endomyocardial biopsies (EMB) is a prerequisite for a definitive diagnosis in ...

Application of machine learning in EEG-based dementia diagnosis: Classification and differential diagnosis.

BackgroundElectroencephalogram (EEG) is a promising, non-invasive method for identifying the presenc...

HIST-DIP: histogram thresholding and deep image priors assisted smartphone-based fluorescence microscopy imaging.

Portable fluorescence microscopes coupled with smartphones offer accessible and cost-effective point...

Performance Evaluation of Artificial Intelligence Techniques in the Diagnosis of Brain Tumors: A Systematic Review and Meta-Analysis.

Brain tumors are becoming more prevalent, often leading to severe disability and high mortality rate...

A visualized machine learning model using noninvasive parameters to differentiate men with and without prostatic carcinoma before biopsy.

This study aimed to create a visualized extreme gradient boosting (XGBOOST) model to distinguish pro...

A machine learning optimized Dielectric Ultra-focused Oscillatory (DUO) electrode for low temperature electrosurgery.

The widespread adoption of radio frequency (RF) energy has made electrosurgery a cornerstone of mode...

Letter to the editor: multichannel deep learning prediction of major pathological response after neoadjuvant immunochemotherapy in lung cancer: a multicenter diagnostic study.

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.

The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is chal...

A variational deep-learning approach to modeling memory T cell dynamics.

Mechanistic models of dynamic, interacting cell populations have yielded many insights into the grow...

A pipeline for mouse brain registration to an atlas after in vivo neurophysiological recordings.

Neurophysiological recordings and histological examinations, along with behavioral observations, are...

Mycophenolate mofetil-induced colitis versus colonic graft-versus-host disease: a comparative histologic study with artificial intelligence model development.

AIM: The aim of this study was to compare the histopathologic features of MMF-induced colitis and co...

Malignancy classification of thyroid incidentalomas using 18F-fluorodeoxy-d-glucose PET/computed tomography-derived radiomics.

BACKGROUND: Thyroid incidentalomas (TIs) are incidental thyroid lesions detected on fluorodeoxy-d-gl...

Advances in postmortem interval estimation: A systematic review of machine learning and metabolomics across various tissue types.

BACKGROUND: Traditional postmortem interval (PMI) estimation methods rely on observable changes such...