AI Medical Compendium Topic:
Bayes Theorem

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Quantitative structure retention relationship (QSRR) modelling for Analytes' retention prediction in LC-HRMS by applying different Machine Learning algorithms and evaluating their performance.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
In metabolomics, retention prediction methods have been developed based on the structural and physicochemical characteristics of analytes. Such methods employ regression models, harnessing machine learning algorithms mapping experimentally derived re...

Gender Identification and Classification of Flies Using Machine Learning Techniques.

Computational and mathematical methods in medicine
is an important genetic model organism used extensively in medical and biological studies. About 61% of known human genes have a recognizable match with the genetic code of Drosophila flies, and 50% of fly protein sequences have mammalian analogues....

Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

Sensors (Basel, Switzerland)
This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays...

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems.

Sensors (Basel, Switzerland)
Power system failures or outages due to short-circuits or "faults" can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, includ...

Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.

Computers in biology and medicine
Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. As a result, rapid and precise identification of COVID-19 patients is critical. Deep Learning has shown promising performance in a variety of domains ...

SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine.

Journal of healthcare engineering
Syndrome differentiation is the most basic diagnostic method in traditional Chinese medicine (TCM). The process of syndrome differentiation is difficult and challenging due to its complexity, diversity, and vagueness. Recently, artificial intelligent...

Research on Multiple Spectral Ranges with Deep Learning for SpO Measurement.

Sensors (Basel, Switzerland)
Oxyhemoglobin saturation by pulse oximetry (SpO) has always played an important role in the diagnosis of symptoms. Considering that the traditional SpO measurement has a certain error due to the number of wavelengths and the algorithm and the wider a...

Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Environmental science & technology
Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimenta...

Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network.

International journal of environmental research and public health
The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified ...

A multi-stage machine learning model for diagnosis of esophageal manometry.

Artificial intelligence in medicine
High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its manual interpretation and classification, including evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based...