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Bayes Theorem

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Application of machine-learning models to predict the ganciclovir and valganciclovir exposure in children using a limited sampling strategy.

Antimicrobial agents and chemotherapy
Intravenous ganciclovir and oral valganciclovir display significant variability in ganciclovir pharmacokinetics, particularly in children. Therapeutic drug monitoring currently relies on the area under the concentration-time (AUC). Machine-learning (...

Constraint based Bayesian optimization of bioink precursor: a machine learning framework.

Biofabrication
Current research practice for optimizing bioink involves exhaustive experimentation with multi-material composition for determining the printability, shape fidelity and biocompatibility. Predicting bioink properties can be beneficial to the research ...

Optimizing protein sequence classification: integrating deep learning models with Bayesian optimization for enhanced biological analysis.

BMC medical informatics and decision making
Efforts to enhance the accuracy of protein sequence classification are of utmost importance in driving forward biological analyses and facilitating significant medical advancements. This study presents a cutting-edge model called ProtICNN-BiLSTM, whi...

Machine learning revealing overlooked conjunction of working volume and mixing intensity in anammox optimization.

Water research
Extensive studies on improving anammox performance have taken place for decades with particular focuses on its operational and environmental factors, but such parameter-based optimization is difficult, because of the sheer number of possible combinat...

Advanced technologies and mathematical metacognition: The present and future orientation.

Bio Systems
The intersection of mathematical cognition, metacognition, and advanced technologies presents a frontier with profound implications for human learning and artificial intelligence. This paper traces the historical roots of these concepts from the Pyth...

DRpred: A Novel Deep Learning-Based Predictor for Multi-Label mRNA Subcellular Localization Prediction by Incorporating Bayesian Inferred Prior Label Relationships.

Biomolecules
The subcellular localization of messenger RNA (mRNA) not only helps us to understand the localization regulation of gene expression but also helps to understand the relationship between RNA localization pattern and human disease mechanism, which has ...

Accurate diagnosis of acute appendicitis in the emergency department: an artificial intelligence-based approach.

Internal and emergency medicine
The diagnosis of abdominal pain in emergency departments is challenging, and appendicitis is a common concern. Atypical symptoms often delay diagnosis. Although the Alvarado score aids in decision-making, its low specificity can lead to unnecessary s...

Confidence-Aware Severity Assessment of Lung Disease from Chest X-Rays Using Deep Neural Network on a Multi-Reader Dataset.

Journal of imaging informatics in medicine
In this study, we present a method based on Monte Carlo Dropout (MCD) as Bayesian neural network (BNN) approximation for confidence-aware severity classification of lung diseases in COVID-19 patients using chest X-rays (CXRs). Trained and tested on 1...

Identifying COVID-19 survivors living with post-traumatic stress disorder through machine learning on Twitter.

Scientific reports
The COVID-19 pandemic has disrupted people's lives and caused significant economic damage around the world, but its impact on people's mental health has not been paid due attention by the research community. According to anecdotal data, the pandemic ...

Identification of medication-related fall risk in adults and older adults admitted to hospital: A machine learning approach.

Geriatric nursing (New York, N.Y.)
The study aimed to develop and validate, through machine learning, a fall risk prediction model related to prescribed medications specific to adults and older adults admitted to hospital. A case-control study was carried out in a tertiary hospital, i...