AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Coloring Agents

Showing 41 to 50 of 89 articles

Clear Filters

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 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...

Learning the Exciton Properties of Azo-dyes.

The journal of physical chemistry letters
The determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine lear...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Scientific reports
Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires ...

Deep learning-based transformation of H&E stained tissues into special stains.

Nature communications
Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly used, special stains can provide additional contrast to different tissue components. Here, we demonstra...

Automated deep learning in ophthalmology: AI that can build AI.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The purpose of this review is to describe the current status of automated deep learning in healthcare and to explore and detail the development of these models using commercially available platforms. We highlight key studies demons...

Stain-free detection of embryo polarization using deep learning.

Scientific reports
Polarization of the mammalian embryo at the right developmental time is critical for its development to term and would be valuable in assessing the potential of human embryos. However, tracking polarization requires invasive fluorescence staining, im...

Automated stain-free histomorphometry of peripheral nerve by contrast-enhancing techniques and artificial intelligence.

Journal of neuroscience methods
BACKGROUND: Traditional histopathologic evaluation of peripheral nerve using brightfield microscopy is resource-intensive, necessitating complex sample preparation. Label-free imaging techniques paired with artificial intelligence-based image reconst...

Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes?

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this article, we provide a convenient tool for all researchers to predict the value of the molar absorption coefficient for a wide number of dyes without any computer costs. The new model is based on RFR method (ALogPS, OEstate + Fragmentor + QNPR...