AIMC Topic: Bayes Theorem

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An ontological analysis of medical Bayesian indicators of performance.

Journal of biomedical semantics
BACKGROUND: Biomedical ontologies aim at providing the most exhaustive and rigorous representation of reality as described by biomedical sciences. A large part of medical reasoning deals with diagnosis and is essentially probabilistic. It would be an...

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

Sensors (Basel, Switzerland)
This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a ...

Sparse Coding and Counting for Robust Visual Tracking.

PloS one
In this paper, we propose a novel sparse coding and counting method under Bayesian framework for visual tracking. In contrast to existing methods, the proposed method employs the combination of L0 and L1 norm to regularize the linear coefficients of ...

Improving diagnostic recognition of primary hyperparathyroidism with machine learning.

Surgery
BACKGROUND: Parathyroidectomy offers the only cure for primary hyperparathyroidism, but today only 50% of primary hyperparathyroidism patients are referred for operation, in large part, because the condition is widely under-recognized. The diagnosis ...

LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length.

BMC bioinformatics
BACKGROUND: Dicer is necessary for the process of mature microRNA (miRNA) formation because the Dicer enzyme cleaves pre-miRNA correctly to generate miRNA with correct seed regions. Nonetheless, the mechanism underlying the selection of a Dicer cleav...

Non-obvious correlations to disease management unraveled by Bayesian artificial intelligence analyses of CMS data.

Artificial intelligence in medicine
OBJECTIVE: Given the availability of extensive digitized healthcare data from medical records, claims and prescription information, it is now possible to use hypothesis-free, data-driven approaches to mine medical databases for novel insight. The goa...

An algorithm for direct causal learning of influences on patient outcomes.

Artificial intelligence in medicine
OBJECTIVE: This study aims at developing and introducing a new algorithm, called direct causal learner (DCL), for learning the direct causal influences of a single target. We applied it to both simulated and real clinical and genome wide association ...

Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

Journal of medical systems
In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving a...

Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Daytime short nap involves physiological processes, such as alertness, drowsiness and sleep. The study of the relationship between drowsiness and nap based on physiological signals is a great way to have a better understanding of the periodical rhyme...

Human Motion Retrieval Based on Statistical Learning and Bayesian Fusion.

PloS one
A novel motion retrieval approach based on statistical learning and Bayesian fusion is presented. The approach includes two primary stages. (1) In the learning stage, fuzzy clustering is utilized firstly to get the representative frames of motions, a...