Pathology

Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.

Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For this retrospective study, DLAD was developed by using 43 292 chest radiographs (normal radiograph-to-nodule radiograph ratio, 34 067:9225) in 34 676 p...

A Convolutional Neural Network Uses Microscopic Images to Differentiate between Mouse and Human Cell Lines and Their Radioresistant Clones.

: Artificial intelligence (AI) trained with a convolutional neural network (CNN) is a recent technological advancement. Previously, several attempts have been made to train AI using medical images for clinical applications. However, whether AI can distinguish microscopic images of mammalian cells has remained debatable. This study assesses the accuracy of image recognition techniques using the CNN...

Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Machine Learning for Molecular Recognition of Myocardial Infarction.

Lipid profile changes in heart muscle have been previously linked to cardiac ischemia and myocardial infarction, but the spatial distribution of lipid...

Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies.

BACKGROUND: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy iden...

Flexible Learning-Free Segmentation and Reconstruction of Neural Volumes.

Imaging is a dominant strategy for data collection in neuroscience, yielding stacks of images that often scale to gigabytes of data for a single exper...

SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis.

Breast cancer is the second leading cause of cancer death among women worldwide. Nevertheless, it is also one of the most treatable malignances if det...

Comprehensive urinary metabolomic characterization of a genetically induced mouse model of prostatic inflammation.

Dysfunction of the lower urinary tract commonly afflicts the middle-aged and aging male population. The etiology of lower urinary tract symptoms (LUTS...

Molecular imaging with neural training of identification algorithm (neural network localization identification).

Superresolution localization microscopy strongly relies on robust identification algorithms for accurate reconstruction of the biological systems it i...

In Silico Prediction of Blood-Brain Barrier Permeability of Compounds by Machine Learning and Resampling Methods.

The blood-brain barrier (BBB) as a part of absorption protects the central nervous system by separating the brain tissue from the bloodstream. In rece...

Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning.

The risk stratification of prostate cancer and breast cancer tumours from patients relies on histopathology, selective genomic testing, or on other me...

A Study of the Role of 180W XPS Lithium Triborate Laser in the Treatment of Patients With Lower Urinary Tracts Symptoms Due to Benign Prostatic Hyperplasia.

Benign prostatic hyperplasia (BPH) is a disease of the prostate commonly seen in elderly males known to cause lower urinary tract symptoms (LUTS) tha...

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the co...

Morphometric Evaluation of the Seminiferous Tubules and the Antioxidant Protective Effects of Gallic Acid and Quercetin in the Testis and Liver of Butyl Phthalate Treated Rats.

The antioxidant protective effects of gallic acid (GAL) and quercetin (QUE) against oxidative stress induced by di-butyl phthalate (DnBP) in the liver...

A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis.

Although alternations of brain functional networks (BFNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been conside...

An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA.

One of the methods for stratifying different molecular classes of breast cancer is the Nottingham prognostic index plus, which uses breast cancer rele...

An EM-based semi-supervised deep learning approach for semantic segmentation of histopathological images from radical prostatectomies.

Automated Gleason grading is an important preliminary step for quantitative histopathological feature extraction. Different from the traditional task ...

Microanalysis of video from a robotic surgical procedure: implications for observational learning in the robotic environment.

Without haptic feedback, robotic surgeons rely on visual processing to interpret the operative field. To provide guidance for teaching in this environ...

Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes.

OBJECTIVE: Support vector machines (SVM) is a newer statistical method that has been reported to be advantageous to traditional logistic regression fo...

Diagnostic performance of real-time robotic arm-assisted F-FDG PET/CT-guided percutaneous biopsy in metabolically active abdominal and pelvic lesions.

PURPOSE: To evaluate the feasibility and diagnostic performance of F-FDG PET/CT-guided biopsy of abdominal and pelvic lesions with automated robotic a...

A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation.

Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft-tissue contrast...