Pathology

Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey.

Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenges in the field of treatment and diagnosis due to its complex biological mechanisms. Early and accurate diagnosis plays a fundamental role in improving survival rates, but the limitations of existing imaging methods and clinical data interpretation often prevent optimal results. Large Language Models...

Using artificial intelligence system for assisting the classification of breast ultrasound glandular tissue components in dense breast tissue.

To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound analysis models for the classification of glandular tissue components (GTC) in dense breast tissue. A total of 1,848 healthy women with mammograms classified as dense breast were enrolled in this prospective study. Residual Network (ResNet) 101 classification model and ResNet with fully Convolutional N...

Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy.

Monitoring and tracking of cell motion is a key component for understanding disease mechanisms and evaluating the effects of treatments. Time-lapse op...

Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles.

Autism spectrum disorder (ASD) presents significant challenges in diagnosis and intervention due to its diverse clinical manifestations and underlying...

Utilisation of Deep Neural Networks for Estimation of Cajal Cells in the Anal Canal Wall of Patients with Advanced Haemorrhoidal Disease Treated by LigaSure Surgery.

Interstitial cells of Cajal (ICCs) play a key role in gastrointestinal smooth muscle contractions, but their relationship with anal canal function in ...

C2BNet: A Deep Learning Architecture With Coupled Composite Backbone for Parasitic Egg Detection in Microscopic Images.

Internet of Medical Things (IoMT) enabled by artificial intelligence (AI) technologies can facilitate automatic diagnosis and management of chronic di...

Prior Visual-Guided Self-Supervised Learning Enables Color Vignetting Correction for High-Throughput Microscopic Imaging.

Vignetting constitutes a prevalent optical degradation that significantly compromises the quality of biomedical microscopic imaging. However, a robust...

A Novel Theranostic Strategy for Malignant Pulmonary Nodules by Targeted CECAM6 with Zr/I-Labeled Tinurilimab.

Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early identification of malignant pulmonary nodules const...

Predicting cell cycle stage from 3D single-cell nuclear-stained images.

The cell cycle governs the proliferation of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research....

A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.

Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichmen...

Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.

Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechani...

3D Hyperspectral Data Analysis with Spatially Aware Deep Learning for Diagnostic Applications.

Nowadays, with the rise of artificial intelligence (AI), deep learning algorithms play an increasingly important role in various traditional fields of...

Development and validation of a framework for registration of whole-mount radical prostatectomy histopathology with three-dimensional transrectal ultrasound.

PURPOSE: Artificial intelligence (AI) has the potential to improve diagnostic imaging on multiple levels. To develop and validate these AI-assisted mo...

5-Repurposed Drug Candidates Identified in Motor Neurons and Muscle Tissues with Amyotrophic Lateral Sclerosis by Network Biology and Machine Learning Based on Gene Expression.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that leads to motor neuron degeneration, muscle weakness, and respirat...

HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization.

Tissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annot...

HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification.

Fine-grained classification of whole slide images (WSIs) is essential in precision oncology, enabling precise cancer diagnosis and personalized treatm...

Urinary biomarkers of kidney transplant rejection.

PURPOSE OF REVIEW: Despite the introduction of many new immunosuppressive medications, allograft rejection remains a significant complication in trans...

Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.

BACKGROUND: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One o...

Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice.

The global burden of cardiovascular diseases continues to rise, making their prevention, diagnosis and treatment increasingly critical. With advanceme...

Enhancing cell instance segmentation in scanning electron microscopy images via a deep contour closing operator.

Accurately segmenting and individualizing cells in scanning electron microscopy (SEM) images is a highly promising technique for elucidating tissue ar...