AIMC Topic: Bayes Theorem

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Force-Sensorless Identification and Classification of Tissue Biomechanical Parameters for Robot-Assisted Palpation.

Sensors (Basel, Switzerland)
The implementation of robotic systems for minimally invasive surgery and medical procedures is an active topic of research in recent years. One of the most common procedures is the palpation of soft tissues to identify their mechanical characteristic...

Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks.

BMC medical informatics and decision making
BACKGROUND: Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 million patients globally. Nearly 40% of patients have uncontrolled seizures yet incur 80% of the cost. Anti-epileptic drugs commonly result in resistance...

Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm.

Scientific reports
To evaluate and establish a prediction model of the outcome of induced labor based on machine learning algorithm. This was a cross-sectional design. The subjects were divided into primipara and multipara, and the risk factors for the outcomes of indu...

Invertible Neural BRDF for Object Inverse Rendering.

IEEE transactions on pattern analysis and machine intelligence
We introduce a novel neural network-based BRDF model and a Bayesian framework for object inverse rendering, i.e., joint estimation of reflectance and natural illumination from a single image of an object of known geometry. The BRDF is expressed with ...

Privacy Preserving Defense For Black Box Classifiers Against On-Line Adversarial Attacks.

IEEE transactions on pattern analysis and machine intelligence
Deep learning models have been shown to be vulnerable to adversarial attacks. Adversarial attacks are imperceptible perturbations added to an image such that the deep learning model misclassifies the image with a high confidence. Existing adversarial...

Bayesian deep learning for error estimation in the analysis of anomalous diffusion.

Nature communications
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in th...

SF High-Voltage Circuit Breaker Contact Status Detection at Different Currents.

Sensors (Basel, Switzerland)
Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact stat...

Comparison of artificial intelligence algorithms and their ranking for the prediction of genetic merit in sheep.

Scientific reports
As the amount of data on farms grows, it is important to evaluate the potential of artificial intelligence for making farming predictions. Considering all this, this study was undertaken to evaluate various machine learning (ML) algorithms using 52-y...

Exploring risk factors for cervical lymph node metastasis in papillary thyroid microcarcinoma: construction of a novel population-based predictive model.

BMC endocrine disorders
BACKGROUND: Machine learning was a highly effective tool in model construction. We aim to establish a machine learning-based predictive model for predicting the cervical lymph node metastasis (LNM) in papillary thyroid microcarcinoma (PTMC).

COVID-19 classification using chest X-ray images based on fusion-assisted deep Bayesian optimization and Grad-CAM visualization.

Frontiers in public health
The COVID-19 virus's rapid global spread has caused millions of illnesses and deaths. As a result, it has disastrous consequences for people's lives, public health, and the global economy. Clinical studies have revealed a link between the severity of...