Pathology

Deep Learning-Based Medical Data Association Rules to Explore the Connectivity and Regulation Mechanism of miRNA-mRNA Network in Myocarditis.

Acute, chronic myocarditis as myocardial localized or diffuse inflammation lesions is usually involving cardiac function in patients with severe adverse outcomes such as heart failure, sudden death, and no unified, but its pathogenesis clinical is mainly composed of a number of factors including infection and autoimmune defects, such as physical and chemical factors; therefore, it is of great sign...

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology.

Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative information from digital histopathology images. AI is expected to reduce workload for human experts, improve the objectivity and consistency of pathology reports, and have a clinical impact by extracting hidden information from routinely available data. Here, we describe how AI can be used to predict canc...

Interpretable deep learning of myelin histopathology in age-related cognitive impairment.

Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbid pathological correlates. Amyloid beta (Aβ) plays...

Microscopic robots with onboard digital control.

Autonomous robots-systems where mechanical actuators are guided through a series of states by information processing units to perform a predesigned fu...

Intelligent Detection and Diagnosis of Power Failure Relying on BP Neural Network Algorithm.

The development of economy and the needs of urban planning have led to the rapid growth of power applications and the corresponding frequent occurrenc...

Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database.

Machine learning has been recently used especially in the medical field. In the diagnosis of serious diseases such as cancer, deep learning techniques...

Automatic Segmentation of Periodontal Tissue Ultrasound Images with Artificial Intelligence: A Novel Method for Improving Dataset Quality.

UNLABELLED: This research aimed to evaluate Mask R-CNN and U-Net convolutional neural network models for pixel-level classification in order to perfor...

A Novel Supervised Filter Feature Selection Method Based on Gaussian Probability Density for Fault Diagnosis of Permanent Magnet DC Motors.

For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domai...

Label-free intraoperative histology of bone tissue via deep-learning-assisted ultraviolet photoacoustic microscopy.

Obtaining frozen sections of bone tissue for intraoperative examination is challenging. To identify the bony edge of resection, orthopaedic oncologist...

Deep learning-based prediction of treatment prognosis from nasal polyp histology slides.

BACKGROUND: Histopathology of nasal polyps contains rich prognostic information, which is difficult to extract objectively. In the present study, we a...

Verbal Autopsy as a Tool for Defining Causes of Death in Specific Healthcare Contexts: Study of Applicability through a Traditional Literature Review.

Autopsy examination, the gold standard for defining causes of death, is often difficult to apply in certain health care settings, especially in develo...

Artificial Intelligence in Spinal Imaging: Current Status and Future Directions.

Spinal maladies are among the most common causes of pain and disability worldwide. Imaging represents an important diagnostic procedure in spinal care...

Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosi...

Automatic whole blood cell analysis from blood smear using label-free multi-modal imaging with deep neural networks.

Whole blood cell analysis is widely used in medical applications since its results are indicators for diagnosing a series of diseases. In this work, w...

Application of Genetic Algorithm and U-Net in Brain Tumor Segmentation and Classification: A Deep Learning Approach.

The development of unusual cells in the cerebrum causes brain cancer. It is classified primarily into two classes: a noncarcinogenic (benign) type of ...

Pancreatic Cancer Detection on CT Scans with Deep Learning: A Nationwide Population-based Study.

Background Approximately 40% of pancreatic tumors smaller than 2 cm are missed at abdominal CT. Purpose To develop and to validate a deep learning (DL...

Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study.

Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI)....

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data.

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local ...

Imaging Orientation of a Single Molecular Hierarchical Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency Generation Microscopy and Neural Network.

In this work, we determined the tilt angles of molecular units in hierarchical self-assembled materials on a single-sheet level, which were not availa...

Artificial intelligence-based classification of peripheral blood nucleated cells using label-free imaging flow cytometry.

Label-free image identification of circulating rare cells, such as circulating tumor cells within peripheral blood nucleated cells (PBNCs), the vast m...