AIMC Topic: Coloring Agents

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Novel navigation for laparoscopic cholecystectomy fusing artificial intelligence and indocyanine green fluorescent imaging.

Journal of hepato-biliary-pancreatic sciences
This preliminary study is the first to demonstrate that AI can precisely identify loose connective tissue during laparoscopic cholecystectomy and ICG fluorescent cholangiography. Tashiro and colleagues conclude that this novel real-time navigation mo...

Integration of lanthanide MOFs/methylcellulose-based fluorescent sensor arrays and deep learning for fish freshness monitoring.

International journal of biological macromolecules
Preserving fish meat poses a significant challenge due to its high protein and low fat content. This study introduces a novel approach that utilizes a common type of lanthanide metal-organic frameworks (Ln-MOFs), EuMOFs, in combination with 5-fluores...

An RNA origami robot that traps and releases a fluorescent aptamer.

Science advances
RNA nanotechnology aims to use RNA as a programmable material to create self-assembling nanodevices for application in medicine and synthetic biology. The main challenge is to develop advanced RNA robotic devices that both sense, compute, and actuate...

Technical and functional design considerations for a real-world interpretable AI solution for NIR perfusion analysis (including cancer).

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Near infrared (NIR) analysis of tissue perfusion via indocyanine green fluorescence assessment is performed clinically during surgery for a range of indications. Its usefulness can potentially be further enhanced through the application of interpreta...

Deep learning-assisted flavonoid-based fluorescent sensor array for the nondestructive detection of meat freshness.

Food chemistry
Gas sensors containing indicators have been widely used in meat freshness testing. However, concerns about the toxicity of indicators have prevented their commercialization. Here, we prepared three fluorescent sensors by complexing each flavonoid (fi...

Quantitative assessment of H&E staining for pathology: development and clinical evaluation of a novel system.

Diagnostic pathology
BACKGROUND: Staining tissue samples to visualise cellular detail and tissue structure is at the core of pathology diagnosis, but variations in staining can result in significantly different appearances of the tissue sample. While the human visual sys...

Application of machine learning-based read-across structure-property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye-sensitized solar cells (DSSCs).

Molecular informatics
The application of various in-silico-based approaches for the prediction of various properties of materials has been an effective alternative to experimental methods. Recently, the concepts of Quantitative structure-property relationship (QSPR) and r...

Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images.

Computers in biology and medicine
Artificial intelligence (AI)-assisted diagnosis is an ongoing revolution in pathology. However, a frequent drawback of AI models is their propension to make decisions based rather on bias in training dataset than on concrete biological features, thus...

Combined colour deconvolution and artificial intelligence approach for region-selective immunohistochemical labelling quantification: The example of alpha smooth muscle actin in mouse kidney.

Journal of biophotonics
Immunohistochemical (IHC) localisation of protein expression is a widely used tool in pathology. This is semi-quantitative and exhibits substantial intra- and inter-observer variability. Digital approaches based on stain quantification applied to IHC...

Color-coded laparoscopic liver resection using artificial intelligence: A preliminary study.

Journal of hepato-biliary-pancreatic sciences
Tashiro and colleagues demonstrated for the first time that an artificial intelligence system can precisely identify intrahepatic vascular structures during laparoscopic liver resection in real time through color coding under bleeding and indocyanine...