AIMC Topic: Algorithms

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Scene-dependent sound event detection based on multitask learning with deformable large kernel attention convolution.

PloS one
Sound event detection (SED) and acoustic scene classification (ASC) are closely related tasks in environmental sound analysis. Given the interrelationship between sound events and scenes, some previous studies have proposed using the multitask learni...

Self-supervised learning framework for efficient classification of endoscopic images using pretext tasks.

PloS one
Identifying anatomical landmarks in endoscopic video frames is essential for the early diagnosis of gastrointestinal diseases. However, this task remains challenging due to variability in visual characteristics across different regions and the limite...

Study on forecasting method of power engineering cost based on BIM and DynGCN.

PloS one
In view of the shortcomings of power engineering cost in precision and dynamic in big data environments, this paper proposes building information modelling (BIM) and spatiotemporal modelling-based dynamic graph convolutional neural networks (DynGCN)....

Deep learning based semantic segmentation of leukemia effected white blood cell.

PloS one
Medical image segmentation has numerous applications in diagnosing different diseases. Various types of diseases are found in white blood and Red blood cells. This paper represents the segmentation of WBCs from blood smear images. It is a complex and...

Application of artificial intelligence in X-ray imaging analysis for knee arthroplasty: A systematic review.

PloS one
BACKGROUND: Artificial intelligence (AI) is a promising and powerful technology with increasing use in orthopedics. The global morbidity of knee arthroplasty is expanding. This study investigated the use of AI algorithms to review radiographs of knee...

Exploring and Identifying Key Factors in Predicting Dyslexia in Children: Advanced Machine Learning Algorithms From Screening to Diagnosis.

Clinical psychology & psychotherapy
INTRODUCTION: The current study aimed to develop and validate a machine learning (ML)-based predictive models for early dyslexia detection in children by integrating neurocognitive, linguistic and behavioural predictors.

Enhancing Medical Image Classification through Transfer Learning and CLAHE Optimization.

Current medical imaging
INTRODUCTION: This paper examines the impact of transfer learning and CLAHE (Contrast Limited Adaptive Histogram Equalization) optimization on the classification of medical images, specifically brain images.

SVM-LncRNAPro: An SVM-Based Method for Predicting Long Noncoding RNA Promoters.

IET systems biology
Long non-coding RNAs (lncRNAs) are closely associated with the regulation of gene expression, whose promoters play a crucial role in comprehensively understanding lncRNA regulatory mechanisms, functions and their roles in diseases. Due to limitations...

Microbial infection disease diagnosis and treatment by artificial intelligence.

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: The main objective of this study was to examine current perspectives on initiatives to identify viable approaches for more accurate diagnosis of infectious diseases.