AIMC Topic: Bayes Theorem
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A fully autonomous robotic ultrasound system for thyroid scanning.
Nature communications
May 11, 2024
The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasou...
Development and application of machine learning models for prediction of soil available cadmium based on soil properties and climate features.
Environmental pollution (Barking, Essex : 1987)
May 10, 2024
Identifying the key influencing factors in soil available cadmium (Cd) is crucial for preventing the Cd accumulation in the food chain. However, current experimental methods and traditional prediction models for assessing available Cd are time-consum...
Improving sepsis classification performance with artificial intelligence algorithms: A comprehensive overview of healthcare applications.
Journal of critical care
May 8, 2024
PURPOSE: This study investigates the potential of machine learning (ML) algorithms in improving sepsis diagnosis and prediction, focusing on their relevance in healthcare decision-making. The primary objective is to contribute to healthcare decision-...
Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.
Chemosphere
May 2, 2024
Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept...
Machine learning-enhanced noninvasive prenatal testing of monogenic disorders.
Prenatal diagnosis
Apr 30, 2024
OBJECTIVE: Single-nucleotide variants (SNVs) are of great significance in prenatal diagnosis as they are the leading cause of inherited single-gene disorders (SGDs). Identifying SNVs in a non-invasive prenatal screening (NIPS) scenario is particularl...
Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning.
Journal of neurotrauma
Apr 29, 2024
Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinatio...
Bidirectional machine learning-assisted sensitivity-based stochastic searching approach for groundwater DNAPL source characterization.
Environmental science and pollution research international
Apr 29, 2024
In this study, we designed a machine learning-based parallel global searching method using the Bayesian inversion framework for efficient identification of dense non-aqueous phase liquid (DNAPL) source characteristics and contaminant transport parame...
Leveraging machine learning: Covariate-adjusted Bayesian adaptive randomization and subgroup discovery in multi-arm survival trials.
Contemporary clinical trials
Apr 28, 2024
Clinical trials evaluate the safety and efficacy of treatments for specific diseases. Ensuring these studies are well-powered is crucial for identifying superior treatments. With the rise of personalized medicine, treatment efficacy may vary based on...
Sorption Behavior of Azo Dye Congo Red onto Activated Biochar from Waste: Gradient Boosting Machine Learning-Assisted Bayesian Optimization for Improved Adsorption Process.
International journal of molecular sciences
Apr 27, 2024
This work aimed to describe the adsorption behavior of Congo red (CR) onto activated biochar material prepared from waste (). The carbon precursor was soaked with phosphoric acid, followed by pyrolysis to convert the precursor into activated biochar...
Construction and validation of an algorithm to separate focal and generalised epilepsy using clinical variables: A comparison of machine learning approaches.
Epilepsy & behavior : E&B
Apr 25, 2024
PURPOSE: Epilepsy type, whether focal or generalised, is important in deciding anti-seizure medication (ASM). In resource-limited settings, investigations are usually not available, so a clinical separation is required. We used a naïve Bayes approach...
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