AI Medical Compendium Topic

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

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Multistain segmentation of renal histology: first steps toward artificial intelligence-augmented digital nephropathology.

Kidney international
Artificial intelligence (AI), and particularly deep learning (DL), are showing great potential in improving pathology diagnostics in many aspects, 1 of which is the segmentation of histology into (diagnostically) relevant compartments. Although most ...

Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.

The Lancet. Oncology
BACKGROUND: Detecting microsatellite instability (MSI) in colorectal cancer is crucial for clinical decision making, as it identifies patients with differential treatment response and prognosis. Universal MSI testing is recommended, but many patients...

Objective Assessment of the Utility of Chromoendoscopy with a Support Vector Machine.

Journal of gastrointestinal cancer
PURPOSE: The utility of chromoendoscopy for early gastric cancer (GC) was determined by machine learning using data of color differences.

Kinetic study of dye removal using TiO supported on polyethylene terephthalate by advanced oxidation processes through neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
This work investigated the efficiency of polyethylene terephthalate (PET) as support material for TiO films in the photocatalytic degradation of red Bordeaux and yellow tartrazine dyes. The optimum operating conditions were determined by a factorial ...

Application of the advanced oxidative process on the degradation of the green leaf and purple açaí food dyes with kinetic monitoring and artificial neural network modelling.

Water science and technology : a journal of the International Association on Water Pollution Research
The study evaluated the advanced oxidative processes concerning the degradation of green leaf and purple açaí dyes, as well as the prediction of data through artificial neural networks (ANNs). It was verified that percentage of degradation on the wav...

Degradation of textile dyes Remazol Yellow Gold and reactive Turquoise: optimization, toxicity and modeling by artificial neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
In this work, the degradation of Remazol Yellow Gold RNL-150% and Reactive Turquoise Q-G125 were investigated using AOP: photolysis, UV/HO, Fenton and photo-Fenton. It was found that the photo-Fenton process employing sunlight radiation was the most ...

An Approach of Anomaly Detection and Neural Network Classifiers to Measure Cellulolytic Activity.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: A common method used for massive detection of cellulolytic microorganisms is based on the formation of halos on solid medium. However, this is a subjective method and real-time monitoring is not possible. The objective of this work...

[Enhanced Treatment of Printing and Dyeing Wastewater Using HO-Biochemical Method].

Huan jing ke xue= Huanjing kexue
The traditional biochemical treatment of printing and dyeing wastewater has limited efficiency. This study investigated whether HO could strengthen the biological ability of the hydrolytic acidification/biological contact oxidation process (A/O), whi...