AIMC Topic: Bayes Theorem

Clear Filters Showing 21 to 30 of 1906 articles

Predicting the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures using machine learning algorithms.

PloS one
OBJECTIVE: To construct and validate a predictive model for the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures based on machine learning algorithms, so as to provide decision-making support for clinic...

Earlier prediction of Parkinson's disease using cross non-decimated wavelet transform and machine learning algorithm.

Scientific reports
Parkinson's disease (PD) is a brain disorder, that affects a person's body movement causing stiffness, shaking and imbalance. Earlier detection of PD is a challenging task for researchers. In this paper, earlier detection of PD is performed using the...

Predicting proximal junctional failure in adult spinal deformity patients using machine learning models based on spinal alignment parameters.

Scientific reports
Proximal junctional failure (PJF) is a significant mechanical complication following corrective surgery for adult spinal deformity (ASD), often resulting in structural failure at the uppermost instrumented vertebra and necessitating revision surgery....

HearteXplain: explainable prediction of acute heart failure and identification of hematologic biomarkers using EBMs and Morris sensitivity analysis.

Scientific reports
Hematological biomarkers have emerged as powerful tools in diagnosing Acute Heart Failure (AHF). This study introduces a novel diagnostic framework that integrates Explainable Artificial Intelligence (XAI) with Morris Sensitivity Analysis (MSA) to en...

TF-crossnet: a cross-modal attention fusion network for cardiovascular disease classification using pcg and ecg signals.

Biomedical physics & engineering express
Electrocardiogram (ECG) and phonocardiogram (PCG) have emerged as crucial non-invasive and portable diagnostic modalities for early cardiovascular disease (CVD) screening. Despite the individual merits of these signal modalities in CVD detection, sig...

Emergent neuronal mechanisms mediating covert attention in convolutional neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Covert visual attention allows the brain to select different regions of the visual world without eye movements. Predictive cues of a target location orient covert attention and improve perceptual performance. In most computational models, researchers...

Comparative evaluation of SNP-weighted, Bayesian, and machine learning models for genomic prediction in Holstein cattle.

BMC genomics
BACKGROUND: Genomic Best Linear Unbiased Prediction (GBLUP) assumes that all SNPs contribute equally to genetic variance, including those with minimal impact, limiting its accuracy. A major challenge in animal breeding is to develop more scientific m...

Refining cancer prediction with DNA sequencing and combined machine learning approaches.

Scientific reports
A high-accuracy DNA-based cancer risk predictor was developed by blending Logistic Regression with Gaussian Naive Bayes, and its hyperparameters were optimized via grid search. Five cancer types (BRCA1, KIRC, COAD, LUAD, PRAD) were classified in a co...

Preoperative plasma ceramide profiling coupled with machine learning accurately predicts recurrence of hepatocellular carcinoma after resection.

Lipids in health and disease
BACKGROUND: Accurate stratification of recurrence risk after curative resection remains a critical challenge in the management of hepatocellular carcinoma (HCC). Dysregulated ceramide (CER) metabolism has been implicated in HCC progression and relaps...

Mortality risk prediction in NSTE-ACS following PCI: Insights from a real-world cohort.

PloS one
BACKGROUND: Non-ST-segment elevation acute coronary syndrome (NSTE-ACS) is a major contributor to cardiovascular mortality, yet reliable tools for individualized mortality prediction remain limited. Machine learning offers the potential to enhance pr...