AI Medical Compendium Topic:
Bayes Theorem

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Advanced Dropout: A Model-Free Methodology for Bayesian Dropout Optimization.

IEEE transactions on pattern analysis and machine intelligence
Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate overfitting and improve the performance of DNNs. The advanced dropout t...

Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search.

IEEE transactions on pattern analysis and machine intelligence
Neural Architecture Search (NAS) has emerged as a promising technique for automatic neural network design. However, existing MCTS based NAS approaches often utilize manually designed action space, which is not directly related to the performance metr...

Machine Learning-Based Intelligent Scoring of College English Teaching in the Field of Natural Language Processing.

Computational intelligence and neuroscience
The current education evaluation is limited not only to the mode of simplification, indexing, and datafication, but also to the scientific nature of college teaching evaluation. This work firstly conducts a theoretical analysis of natural language pr...

Lifelong Incremental Reinforcement Learning With Online Bayesian Inference.

IEEE transactions on neural networks and learning systems
A central capability of a long-lived reinforcement learning (RL) agent is to incrementally adapt its behavior as its environment changes and to incrementally build upon previous experiences to facilitate future learning in real-world scenarios. In th...

Scalable Inverse Reinforcement Learning Through Multifidelity Bayesian Optimization.

IEEE transactions on neural networks and learning systems
Data in many practical problems are acquired according to decisions or actions made by users or experts to achieve specific goals. For instance, policies in the mind of biologists during the intervention process in genomics and metagenomics are often...

Using Healthcare Resources Wisely: A Predictive Support System Regarding the Severity of Patient Falls.

Journal of healthcare engineering
BACKGROUND: An injurious fall is one of the main indicators of care quality in healthcare facilities. Despite several fall screen tools being widely used to evaluate a patient's fall risk, they are frequently unable to reveal the severity level of pa...

Utilization of artificial intelligence approach for prediction of DLP values for abdominal CT scans: A high accuracy estimation for risk assessment.

Frontiers in public health
PURPOSE: This study aimed to evaluate Artificial Neural Network (ANN) modeling to estimate the significant dose length product (DLP) value during the abdominal CT examinations for quality assurance in a retrospective, cross-sectional study.

Classification and Detection of Mesothelioma Cancer Using Feature Selection-Enabled Machine Learning Technique.

BioMed research international
Cancer of the mesothelium, sometimes referred to as malignant mesothelioma (MM), is an extremely uncommon form of the illness that almost always results in death. Chemotherapy, surgery, radiation therapy, and immunotherapy are all potential treatment...

Detection of Pancreatic Cancer in CT Scan Images Using PSO SVM and Image Processing.

BioMed research international
A diagnosis of pancreatic cancer is one of the worst cancers that may be received anywhere in the world; the five-year survival rate is very less. The majority of cases of this condition may be traced back to pancreatic cancer. Due to medical image s...

BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images.

Sensors (Basel, Switzerland)
Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment of ALL is strongly associated with the early diagnosis of the disease. Current pract...