Pathology

Attention Mask R-CNN with edge refinement algorithm for identifying circulating genetically abnormal cells.

Recent studies have suggested that circulating tumor cells with abnormalities in gene copy numbers in mononuclear cell-enriched peripheral blood samples, such as circulating genetically abnormal cells (CACs), can be used as a non-invasive tool to detect patients with benign pulmonary nodules. These cells are identified through fluorescence signals counting by using 4-color fluorescence in situ hyb...

Nuclear morphology is a deep learning biomarker of cellular senescence.

Cellular senescence is an important factor in aging and many age-related diseases, but understanding its role in health is challenging due to the lack of exclusive or universal markers. Using neural networks, we predict senescence from the nuclear morphology of human fibroblasts with up to 95% accuracy, and investigate murine astrocytes, murine neurons, and fibroblasts with premature aging in cult...

Characterization of the SGLT2 Interaction Network and Its Regulation by SGLT2 Inhibitors: A Bioinformatic Analysis.

Sodium-glucose cotransporter 2 (SGLT2), also known as solute carrier family 5 member 2 (SLC5A2), is a promising target for a new class of drugs prima...

Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis.

Machine learning (ML) algorithms are becoming increasingly pervasive in the domains of medical diagnostics and prognostication, afforded by complex de...

Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.

Tumor segmentation is a fundamental task in histopathological image analysis. Creating accurate pixel-wise annotations for such segmentation tasks in ...

Development and multi-institutional validation of an artificial intelligence-based diagnostic system for gastric biopsy.

To overcome the increasing burden on pathologists in diagnosing gastric biopsies, we developed an artificial intelligence-based system for the patholo...

Boundary-aware glomerulus segmentation: Toward one-to-many stain generalization.

The growing availability of scanned whole-slide images (WSIs) has allowed nephropathology to open new possibilities for medical decision-making over h...

Deep learning-based diagnosis from endobronchial ultrasonography images of pulmonary lesions.

Endobronchial ultrasonography with a guide sheath (EBUS-GS) improves the accuracy of bronchoscopy. The possibility of differentiating benign from mali...

De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks.

With the emergence of high throughput single cell techniques, the understanding of the molecular and cellular diversity of mammalian organs have rapid...

A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.

BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and w...

Self-Supervised Transfer Learning Based on Domain Adaptation for Benign-Malignant Lung Nodule Classification on Thoracic CT.

The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung cancer diagnosis. Compared with 2D nodule CT images, the...

Quantifying the post-radiation accelerated brain aging rate in glioma patients with deep learning.

BACKGROUND AND PURPOSE: Changes of healthy appearing brain tissue after radiotherapy (RT) have been previously observed. Patients undergoing RT may ha...

An effective automatic segmentation of abdominal adipose tissue using a convolution neural network.

BACKGROUND AND AIMS: Computer-aided diagnosis and prognosis rely heavily on fully automatic segmentation of abdominal fat tissue using Emission Tomogr...

Automated Recognition of Cancer Tissues through Deep Learning Framework from the Photoacoustic Specimen.

The fast advancement of biomedical research technology has expanded and enhanced the spectrum of diagnostic instruments. Various research groups have ...

Predicting the Likelihood of Colorectal Cancer with Artificial Intelligence Tools Using Fourier Transform Infrared Signals Obtained from Tumor Samples.

The early and accurate detection of colorectal cancer (CRC) significantly affects its prognosis and clinical management. However, current standard dia...

Deep multi-scale resemblance network for the sub-class differentiation of adrenal masses on computed tomography images.

OBJECTIVE: The accurate classification of mass lesions in the adrenal glands ('adrenal masses'), detected with computed tomography (CT), is important ...

Intelligent nanoscope for rapid nanomaterial identification and classification.

Machine learning image recognition and classification of particles and materials is a rapidly expanding field. However, nanomaterial identification an...

A real-time object detection model for orchard pests based on improved YOLOv4 algorithm.

Accurate and efficient real-time detection of orchard pests was essential and could improve the economic benefits of the fruit industry. The orchard p...

Sampling Based Tumor Recognition in Whole-Slide Histology Image With Deep Learning Approaches.

Histopathological identification of tumor tissue is one of the routine pathological diagnoses for pathologists. Recently, computational pathology has ...

TSDLPP: A Novel Two-Stage Deep Learning Framework For Prognosis Prediction Based on Whole Slide Histopathological Images.

Recently, digital pathology image-based prognosis prediction has become a hot topic in healthcare research to make early decisions on therapy and impr...