AIMC Topic: Bayes Theorem

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Leveraging machine learning: Covariate-adjusted Bayesian adaptive randomization and subgroup discovery in multi-arm survival trials.

Contemporary clinical trials
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
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
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...

Predicting FFAR4 agonists using structure-based machine learning approach based on molecular fingerprints.

Scientific reports
Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigatin...

Developing an interpretation model for body fluid identification.

Forensic science international
Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenar...

Sequence based model using deep neural network and hybrid features for identification of 5-hydroxymethylcytosine modification.

Scientific reports
RNA modifications are pivotal in the development of newly synthesized structures, showcasing a vast array of alterations across various RNA classes. Among these, 5-hydroxymethylcytosine (5HMC) stands out, playing a crucial role in gene regulation and...

Advancing post-traumatic seizure classification and biomarker identification: Information decomposition based multimodal fusion and explainable machine learning with missing neuroimaging data.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
A late post-traumatic seizure (LPTS), a consequence of traumatic brain injury (TBI), can potentially evolve into a lifelong condition known as post-traumatic epilepsy (PTE). Presently, the mechanism that triggers epileptogenesis in TBI patients remai...

DNA shape features improve prediction of CRISPR/Cas9 activity.

Methods (San Diego, Calif.)
The CRISPR/Cas9 genome editing technology has transformed basic and translational research in biology and medicine. However, the advances are hindered by off-target effects and a paucity in the knowledge of the mechanism of the Cas9 protein. Machine ...

Deep neural network uncertainty estimation for early oral cancer diagnosis.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
BACKGROUND: Early diagnosis in oral cancer is essential to reduce both morbidity and mortality. This study explores the use of uncertainty estimation in deep learning for early oral cancer diagnosis.

Comparison of mandibular morphometric parameters in digital panoramic radiography in gender determination using machine learning.

Oral radiology
OBJECTIVE: This study aimed to evaluate the usability of morphometric features obtained from mandibular panoramic radiographs in gender determination using machine learning algorithms.