AIMC Topic: Algorithms

Clear Filters Showing 8531 to 8540 of 28713 articles

Enhancing and improving the performance of imbalanced class data using novel GBO and SSG: A comparative analysis.

Neural networks : the official journal of the International Neural Network Society
Class imbalance problem (CIP) in a dataset is a major challenge that significantly affects the performance of Machine Learning (ML) models resulting in biased predictions. Numerous techniques have been proposed to address CIP, including, but not limi...

Optimised stacked machine learning algorithms for genomics and genetics disorder detection in the healthcare industry.

Functional & integrative genomics
With recent advances in precision medicine and healthcare computing, there is an enormous demand for developing machine learning algorithms in genomics to enhance the rapid analysis of disease disorders. Technological advancement in genomics and imag...

Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

Environmental science and pollution research international
The breathtaking economic development put a heavy toll on ecology, especially on water pollution. Efficient water resource management has a long-term influence on the sustainable development of the economy and society. Economic development and ecolog...

Bayesian hypernetwork collaborates with time-difference evolutional network for temporal knowledge prediction.

Neural networks : the official journal of the International Neural Network Society
A Temporal Knowledge Graph (TKG) is a sequence of Knowledge Graphs (KGs) attached with time information, in which each KG contains the facts that co-occur at the same timestamp. Temporal knowledge prediction (TKP) aims to predict future events given ...

Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.

Magma (New York, N.Y.)
OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with o...

Deep Learning Models Used in the Diagnostic Workup of Keratoconus: A Systematic Review and Exploratory Meta-Analysis.

Cornea
PURPOSE: The prevalence of keratoconus in the general population is reported to be up to 1 of 84. Over the past 2 decades, diagnosis and management evolved rapidly, but keratoconus screening in clinical practice is still challenging and asks for impr...

A physically constrained Monte Carlo-Neural Network coupling algorithm for BNCT dose calculation.

Medical physics
BACKGROUND: In boron neutron capture therapy (BNCT)-a form of binary radiotherapy-the primary challenge in treatment planning systems for dose calculations arises from the time-consuming nature of the Monte Carlo (MC) method. Recent progress, includi...

Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.

American journal of ophthalmology
PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may...

Data-driven learning of chaotic dynamical systems using Discrete-Temporal Sobolev Networks.

Neural networks : the official journal of the International Neural Network Society
We introduce the Discrete-Temporal Sobolev Network (DTSN), a neural network loss function that assists dynamical system forecasting by minimizing variational differences between the network output and the training data via a temporal Sobolev norm. Th...

Potential cognitive risks of generative transformer-based AI chatbots on higher order executive functions.

Neuropsychology
BACKGROUND: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use...