AIMC Topic: Bayes Theorem

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Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms.

Scientific reports
Microorganisms are one of the most promising biomarkers for cancer, and the relationship between microorganisms and lung cancer occurrence and development provides significant potential for pulmonary nodule (PN) diagnosis from a microbiological persp...

A Framework for Parameter Estimation and Uncertainty Quantification in Systems Biology Using Quantile Regression and Physics-Informed Neural Networks.

Bulletin of mathematical biology
A framework for parameter estimation and uncertainty quantification is crucial for understanding the mechanisms of biological interactions within complex systems and exploring their dynamic behaviors beyond what can be experimentally observed. Despit...

Optimal cybersecurity framework for smart water system: Detection, localization and severity assessment.

Water research
The digital transformation of water distribution systems has streamlined monitoring and control through the integration of smart devices such as pressure sensors, smart meters, and level switches, all communicating with supervisory control and data a...

Enhancing prediction and stratifying risk: machine learning and bayesian-learning models for catheter-related thrombosis in chemotherapy patients.

BMC cancer
BACKGROUND: Catheter-related thrombosis (CRT) is a serious complication in cancer patients undergoing chemotherapy, yet existing risk prediction models demonstrate limited accuracy. This study aimed to evaluate the clinical utility of machine learnin...

Exploring new drug treatment targets for immune related bone diseases using a multi omics joint analysis strategy.

Scientific reports
In the field of treatment and prevention of immune-related bone diseases, significant challenges persist, necessitating the urgent exploration of new and effective treatment methods. However, most existing Mendelian randomization (MR) studies are con...

Intelligent progress monitoring of healing wound tissues based on classification models.

Biomedical physics & engineering express
The evolution of wound monitoring techniques has seen a significant shift from traditional methods like ruler-based measurements to the use of AI-assisted assessment of wound tissues. This progression has been driven by the need for more accurate, ef...

A Hybrid ODE-NN Framework for Modeling Incomplete Physiological Systems.

IEEE transactions on bio-medical engineering
This paper proposes a method to learn approximations of missing Ordinary Differential Equations (ODEs) and states in physiological models where knowledge of the system's relevant states and dynamics is incomplete. The proposed method augments known O...

PULSE: A DL-Assisted Physics-Based Approach to the Inverse Problem of Electrocardiography.

IEEE transactions on bio-medical engineering
This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) methods. Our objective is to enhance the accuracy and robustness of ECGI reconstructions. We reshape the ...

Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy.

Scientific reports
New bronchoscopy techniques like radial probe endobronchial ultrasound have been developed for real-time sampling characterization, but their use is still limited. This study aims to use classification algorithms with minimally invasive electrical im...