Pathology

A novel deep learning-based method for automatic stereology of microglia cells from low magnification images.

Microglial cells mediate diverse homeostatic, inflammatory, and immune processes during normal development and in response to cytotoxic challenges. During these functional activities, microglial cells undergo distinct numerical and morphological changes in different tissue volumes in both rodent and human brains. However, it remains unclear how these cytostructural changes in microglia correlate w...

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy.

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population found in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory...

Artificial intelligence's impact on breast cancer pathology: a literature review.

This review discusses the profound impact of artificial intelligence (AI) on breast cancer (BC) diagnosis and management within the field of pathology...

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning.

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determinatio...

Robot-assisted thoracic surgery for benign tumors at the cervicothoracic junction: a propensity-matched study.

This study aimed to assess the feasibility and safety of robot-assisted thoracic surgery (RATS) for resecting benign tumors of the cervicothoracic jun...

A journey from omics to clinicomics in solid cancers: Success stories and challenges.

The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations...

Initial Experience in Urological Surgery with a Novel Robotic Technology: Magnetic-Assisted Robotic Surgery in Urology.

Magnetic-assisted robotic surgery (MARS) has been developed to maximize patient benefits of minimally invasive surgery while enhancing surgeon contro...

Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning.

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailabi...

Real-Time Tissue Classification Using a Novel Optical Needle Probe for Biopsy.

Core needle biopsy is a part of the histopathological process, which is required for cancerous tissue examination. The most common method to guide the...

A Histopathologic Image Analysis for the Classification of Endocervical Adenocarcinoma Silva Patterns Depend on Weakly Supervised Deep Learning.

Twenty-five percent of cervical cancers are classified as endocervical adenocarcinomas (EACs), which comprise a highly heterogeneous group of tumors. ...

Deep learning applications for kidney histology analysis.

PURPOSE OF REVIEW: Nephropathology is increasingly incorporating computational methods to enhance research and diagnostic accuracy. The widespread ado...

Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3.

BACKGROUND: For patients with PI-RADS v2.1 ≥ 3, prostate biopsy is strongly recommended. Due to the unsatisfactory positive rate of biopsy, improvemen...

A Molecular Typing Method for Invasive Breast Cancer by Serum Raman Spectroscopy.

BACKGROUND: The incidence of breast cancer ranks highest among cancers and is exceedingly heterogeneous. Immunohistochemical staining is commonly used...

Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors.

Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The ...

Effects of various cross-linked collagen scaffolds on wound healing in rats model by deep-learning CNN.

Scar tissue is connective tissue formed on the wound during the wound-healing process. The most significant distinction between scar tissue and normal...

Computational drug development for membrane protein targets.

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep lea...

Identification of Hit Compounds Using Artificial Intelligence for the Management of Allergic Diseases.

This study aimed to identify and evaluate drug candidates targeting the kinase inhibitory region of suppressor of cytokine signaling (SOCS) 3 for the ...

Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization.

The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious liver condition, are crucial for effective medical...

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.

Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of dis...

METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images.

BACKGROUND: Mesenchymal epithelial transformation (MET) is a key molecular target for diagnosis and treatment of non-small cell lung cancer (NSCLC). T...