AIMC Topic: Coloring Agents

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A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores.

Scientific reports
We examined whether a tool for determining Johnsen scores automatically using artificial intelligence (AI) could be used in place of traditional Johnsen scoring to support pathologists' evaluations. Average precision, precision, and recall were asses...

An adaptive digital stain separation method for deep learning-based automatic cell profile counts.

Journal of neuroscience methods
BACKGROUND: Quantifying cells in a defined region of biological tissue is critical for many clinical and preclinical studies, especially in the fields of pathology, toxicology, cancer and behavior. As part of a program to develop accurate, precise an...

Hg(II) sensing, catalytic, antioxidant, antimicrobial, and anticancer potential of Garcinia mangostana and α-mangostin mediated silver nanoparticles.

Chemosphere
This study reports synthesis of Garcinia mangostana fruit pericarp (unwanted waste material) and α-mangostin mediated silver nanoparticles (AgNPs). These AgNPs were efficiently produced using 1:10 (extract and salt) ratio under stirring and heating, ...

A deep learning diagnostic platform for diffuse large B-cell lymphoma with high accuracy across multiple hospitals.

Nature communications
Diagnostic histopathology is a gold standard for diagnosing hematopoietic malignancies. Pathologic diagnosis requires labor-intensive reading of a large number of tissue slides with high diagnostic accuracy equal or close to 100 percent to guide trea...

SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning.

Scientific reports
Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we presen...

Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks.

Advanced materials (Deerfield Beach, Fla.)
Artificial scent screening systems (known as electronic noses, E-noses) have been researched extensively. A portable, automatic, and accurate, real-time E-nose requires both robust cross-reactive sensing and fingerprint pattern recognition. Few E-nos...

Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis.

Tuberculosis (Edinburgh, Scotland)
Of all bacterial infectious diseases, infection by Mycobacterium tuberculosis poses one of the highest morbidity and mortality burdens on humans throughout the world. Due to its speed and cost-efficiency, manual microscopy of auramine-stained sputum ...

Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.

Kidney international
The application of deep learning for automated segmentation (delineation of boundaries) of histologic primitives (structures) from whole slide images can facilitate the establishment of novel protocols for kidney biopsy assessment. Here, we developed...

Classification of pachychoroid disease on ultrawide-field indocyanine green angiography using auto-machine learning platform.

The British journal of ophthalmology
AIMS: Automatic identification of pachychoroid maybe used as an adjunctive method to confirm the condition and be of help in treatment for macular diseases. This study investigated the feasibility of classifying pachychoroid disease on ultra-widefiel...