Pathology

Optical coherence tomography for identification of malignant pulmonary nodules based on random forest machine learning algorithm.

OBJECTIVE: To explore the feasibility of using random forest (RF) machine learning algorithm in assessing normal and malignant peripheral pulmonary nodules based on in vivo endobronchial optical coherence tomography (EB-OCT).

Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed the development of high-performance algorithms th...

Digital Technology in Diagnostic Breast Pathology and Immunohistochemistry.

Digital technology has been used in the field of diagnostic breast pathology and immunohistochemistry (IHC) for decades. Examples include automated ti...

SAFRON: Stitching Across the Frontier Network for Generating Colorectal Cancer Histology Images.

Automated synthesis of histology images has several potential applications including the development of data-efficient deep learning algorithms. In th...

Generative Adversarial Networks for Morphological-Temporal Classification of Stem Cell Images.

Frequently, neural network training involving biological images suffers from a lack of data, resulting in inefficient network learning. This issue ste...

Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.

The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). Th...

Deep learning based cervical screening by the cross-modal integration of colposcopy, cytology, and HPV test.

PURPOSE: To develop and evaluate the colposcopy based deep learning model using all kinds of cervical images for cervical screening, and investigate t...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosy...

Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry.

Semi-quantitative scoring is a method that is widely used to estimate the quantity of proteins on chromogen-labelled immunohistochemical (IHC) tissue ...

Automated Hyperspectral 2D/3D Raman Analysis Using the Learner-Predictor Strategy: Machine Learning-Based Inline Raman Data Analytics.

Synchronously detecting multiple Raman spectral signatures in two-dimensional/three-dimensional (2D/3D) hyperspectral Raman analysis is a daunting cha...

A survey on graph-based deep learning for computational histopathology.

With the remarkable success of representation learning for prediction problems, we have witnessed a rapid expansion of the use of machine learning and...

Weakly-supervised deep learning for ultrasound diagnosis of breast cancer.

Conventional deep learning (DL) algorithm requires full supervision of annotating the region of interest (ROI) that is laborious and often biased. We ...

Morphological features of single cells enable accurate automated classification of cancer from non-cancer cell lines.

Accurate cancer detection and diagnosis is of utmost importance for reliable drug-response prediction. Successful cancer characterization relies on bo...

A Preliminary Investigation on the Antiviral Activities of the Philippine Marshmint (Mentha arvensis) Leaf Extracts against Dengue Virus Serotype 2 In Vitro.

In this study, we investigated the antiviral activity of lyophilized crude leaf extracts of the Philippine marshmint (Mentha arvensis L., commonly cal...

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.

Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to...

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation.

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegene...

Single-Port Robotic Inguinal Lymph Node Dissection for Penile Cancer.

OBJECTIVE: Inguinal lymph node dissection (ILND) is an essential component in the diagnosis, management, and treatment of penile cancer. Recent advanc...

Brain tissue segmentation via non-local fuzzy c-means clustering combined with Markov random field.

The segmentation and extraction of brain tissue in magnetic resonance imaging (MRI) is a meaningful task because it provides a diagnosis and treatment...

The use and applicability of machine learning algorithms in predicting the surgical outcome for patients with benign prostatic enlargement. Which model to use?

OBJECTIVES: Artificial intelligence (AI) is increasingly used in medicine, but data on benign prostatic enlargement (BPE) management are lacking. This...

Computed tomography radiomics for the prediction of thymic epithelial tumor histology, TNM stage and myasthenia gravis.

OBJECTIVES: To evaluate CT-derived radiomics for machine learning-based classification of thymic epithelial tumor (TET) stage (TNM classification), hi...