AI Medical Compendium Topic

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

Microscopy

Showing 21 to 30 of 561 articles

Clear Filters

"UDE DIATOMS in the Wild 2024": a new image dataset of freshwater diatoms for training deep learning models.

GigaScience
BACKGROUND: Diatoms are microalgae with finely ornamented microscopic silica shells. Their taxonomic identification by light microscopy is routinely used as part of community ecological research as well as ecological status assessment of aquatic ecos...

Enhanced Detection of Leishmania Parasites in Microscopic Images Using Machine Learning Models.

Sensors (Basel, Switzerland)
Cutaneous leishmaniasis is a parasitic disease that poses significant diagnostic challenges due to the variability of results and reliance on operator expertise. This study addresses the development of a system based on machine learning algorithms to...

Unsupervised inter-domain transformation for virtually stained high-resolution mid-infrared photoacoustic microscopy using explainable deep learning.

Nature communications
Mid-infrared photoacoustic microscopy can capture biochemical information without staining. However, the long mid-infrared optical wavelengths make the spatial resolution of photoacoustic microscopy significantly poorer than that of conventional conf...

Development of deep learning-based mobile application for the identification of Coccidia species in pigs using microscopic images.

Veterinary parasitology
Coccidiosis is a gastrointestinal parasitic disease caused by different species of Eimeria and Isospora, poses a significant threat to pig farming, leading to substantial economic losses attributed to reduced growth rates, poor feed conversion, incre...

Let it shine: Autofluorescence of Papanicolaou-stain improves AI-based cytological oral cancer detection.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: Oral cancer is a global health challenge. The disease can be successfully treated if detected early, but the survival rate drops significantly for late stage cases. There is a growing interest in a shift from the current st...

Diagnosis of infections using artificial intelligence techniques versus standard microscopy in a reference laboratory.

Journal of clinical microbiology
Diagnosing malaria using standard techniques is time-consuming. With limited staffing in many laboratories, this may lead to delays in reporting. Innovative technologies are changing the diagnostic landscape and may help alleviate staffing shortages....

Representative training data sets are critical for accurate machine-learning classification of microscopy images of particles formed by lipase-catalyzed polysorbate hydrolysis.

Journal of pharmaceutical sciences
Polysorbate 20 (PS20) is commonly used as an excipient in therapeutic protein formulations. However, over the course of a therapeutic protein product's shelf life, minute amounts of co-purified host-cell lipases may cause slow hydrolysis of PS20, rel...

Virtual Gram staining of label-free bacteria using dark-field microscopy and deep learning.

Science advances
Gram staining has been a frequently used staining protocol in microbiology. It is vulnerable to staining artifacts due to, e.g., operator errors and chemical variations. Here, we introduce virtual Gram staining of label-free bacteria using a trained ...

A novel approach in cancer diagnosis: integrating holography microscopic medical imaging and deep learning techniques-challenges and future trends.

Biomedical physics & engineering express
Medical imaging is pivotal in early disease diagnosis, providing essential insights that enable timely and accurate detection of health anomalies. Traditional imaging techniques, such as Magnetic Resonance Imaging (MRI), Computer Tomography (CT), ult...

Image-based fuzzy logic control for pressure-driven droplet microfluidics as autosampler for multimodal imaging microscopy.

Lab on a chip
Here we present a highly customisable image-based fuzzy logic control (FLC) method for pressure-driven droplet microfluidics. The system is designed to position droplets of different sizes in microfluidic chips of varying channel size in the centre o...