AIMC Topic: Algorithms

Clear Filters Showing 9121 to 9130 of 28713 articles

Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules.

Journal of chemical information and modeling
We introduce an exploratory active learning (AL) algorithm using Gaussian process regression and marginalized graph kernel (GPR-MGK) to sample chemical compound space (CCS) at minimal cost. Targeting 251,728 enumerated alkane molecules with 4-19 carb...

Novel Solution for Using Neural Networks for Kidney Boundary Extraction in 2D Ultrasound Data.

Biomolecules
: Kidney ultrasound (US) imaging is a significant imaging modality for evaluating kidney health and is essential for diagnosis, treatment, surgical intervention planning, and follow-up assessments. Kidney US image segmentation consists of extracting ...

Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms.

BMC medical informatics and decision making
INTRODUCTION: The global society is currently facing a rise in the elderly population. The concept of successful aging (SA) appeared in the gerontological literature to overcome the challenges and problems of population aging. SA is a subjective and ...

Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals.

BMC medical informatics and decision making
BACKGROUND: Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically, ECG machines are utilized to diagnose and monitor cardiac arrhythmia n...

On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.

PloS one
Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains ...

Voice pathology detection using optimized convolutional neural networks and explainable artificial intelligence-based analysis.

Computer methods in biomechanics and biomedical engineering
This article proposes a noninvasive computer-aided assessment approach based on optimized convolutional neural network for healthy and pathological voice detection. Firstly, the input voice samples are first transformed into mel-spectrogram time-freq...

Taylor Remora optimization enabled deep learning algorithms for percentage of pesticide detection in grapes.

Environmental science and pollution research international
In the world, grapes are considered as the most significant fruit, and it comprises various nutrients, like Vitamin C and it is utilized to produce wines and raisins. The major six general grape leaf diseases and pests are brown spots, leaf blight, d...

Machine learning model to predict the width of maxillary central incisor from anthropological measurements.

Journal of prosthodontic research
PURPOSE: To improve smile esthetics, clinicians should comprehensively analyze the face and ensure that the sizes selected for the maxillary anterior teeth are compatible with the available anthropological measurements. The inter commissural (ICW), i...

Deep learning-based identification of spine growth potential on EOS radiographs.

European radiology
OBJECTIVES: To develop an automatic computer-based method that can help clinicians in assessing spine growth potential based on EOS radiographs.

Artificial intelligence in osteoarthritis detection: A systematic review and meta-analysis.

Osteoarthritis and cartilage
OBJECTIVES: As an increasing number of studies apply artificial intelligence (AI) algorithms in osteoarthritis (OA) detection, we performed a systematic review and meta-analysis to pool the data on diagnostic performance metrics of AI, and to compare...