AIMC Topic: Algorithms

Clear Filters Showing 4851 to 4860 of 28713 articles

NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation.

Science robotics
To achieve human-level dexterity, robots must infer spatial awareness from multimodal sensing to reason over contact interactions. During in-hand manipulation of novel objects, such spatial awareness involves estimating the object's pose and shape. T...

Harnessing hybrid deep learning approach for personalized retrieval in e-learning.

PloS one
The current worldwide pandemic has significantly increased the need for online learning platforms, hence presenting difficulty in choosing appropriate course materials from the vast online educational resources due to user knowledge frameworks variat...

Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients.

Biomarkers in medicine
Inflammatory prognostic index (IPI), has been shown to be related with poor outcomes in cancer patients. We aimed to investigate the predictive role of IPI for contrast-induced nephropathy (CIN) development in non-ST segment elevation myocardial inf...

Classification models and SAR analysis of anaplastic lymphoma kinase (ALK) inhibitors using machine learning algorithms with two data division methods.

Molecular diversity
Anaplastic lymphoma kinase (ALK) plays a critical role in the development of various cancers. In this study, the dataset of 1810 collected inhibitors were divided into a training set and a test set by the self-organizing map (SOM) and random method, ...

Drug Sensitivity Prediction Based on Multi-stage Multi-modal Drug Representation Learning.

Interdisciplinary sciences, computational life sciences
Accurate prediction of anticancer drug responses is essential for developing personalized treatment plans in order to improve cancer patient survival rates and reduce healthcare costs. To this end, we propose a drug sensitivity prediction model based...

FlexPoints: Efficient electrocardiogram signal compression for machine learning.

Journal of electrocardiology
The electrocardiogram (ECG) stands out as one of the most frequently used medical tests, playing a crucial role in the accurate diagnosis and treatment of patients. While ECG devices generate a huge amount of data, only a fraction of it holds valuabl...

UMS-ODNet: Unified-scale domain adaptation mechanism driven object detection network with multi-scale attention.

Neural networks : the official journal of the International Neural Network Society
Unsupervised domain adaptation techniques improve the generalization capability and performance of detectors, especially when the source and target domains have different distributions. Compared with two-stage detectors, one-stage detectors (especial...

Recognizing and explaining driving stress using a Shapley additive explanation model by fusing EEG and behavior signals.

Accident; analysis and prevention
Driving stress is a critical factor leading to road traffic accidents. Despite numerous studies that have been conducted on driving stress recognition, most of them only focus on accuracy improvement without taking model interpretability into account...

Using advanced machine learning algorithms to predict academic major completion: A cross-sectional study.

Computers in biology and medicine
BACKGROUND: Existing prediction methods for academic majors based on personality traits have notable gaps, including limited model complexity and generalizability.The current study aimed to utilize advanced Machine Learning (ML) algorithms with smoot...

MultiADE: A Multi-domain benchmark for Adverse Drug Event extraction.

Journal of biomedical informatics
OBJECTIVE: Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data sources, such as electronic health records, medical literature, social media and search engine logs. Over the years, many datasets have been created, ...