AIMC Topic: Algorithms

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Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society.

PloS one
Informal education via social media plays a crucial role in modern learning, offering self-directed and community-driven opportunities to gain knowledge, skills, and attitudes beyond traditional educational settings. These platforms provide access to...

Extended DEMATEL method with intuitionistic fuzzy information: A case of electric vehicles.

PloS one
The Decision-Making Trial and Laboratory (DEMATEL) methodology excels in the analysis of interdependent factors within complex systems, with correlation data typically presented in crisp values. Nevertheless, the judgments made by decision-makers oft...

A novel machine learning model for perimeter intrusion detection using intrusion image dataset.

PloS one
Perimeter Intrusion Detection Systems (PIDS) are crucial for protecting any physical locations by detecting and responding to intrusions around its perimeter. Despite the availability of several PIDS, challenges remain in detection accuracy and preci...

DDP-DAR: Network intrusion detection based on denoising diffusion probabilistic model and dual-attention residual network.

Neural networks : the official journal of the International Neural Network Society
Network intrusion detection (NID) is an effective manner to guarantee the security of cyberspace. However, the scale of normal network traffic is much larger than intrusion traffic (i.e., appearing data imbalance problem), which leads to the training...

CMFX: Cross-modal fusion network for RGB-X crowd counting.

Neural networks : the official journal of the International Neural Network Society
Currently, for obtaining more accurate counts, existing methods primarily utilize RGB images combined with features of complementary modality (X-modality) for counting. However, designing a model that can adapt to various sensors is still an unsolved...

A Machine Learning Model to Predict De Novo Hepatocellular Carcinoma Beyond Year 5 of Antiviral Therapy in Patients With Chronic Hepatitis B.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: This study aims to develop and validate a machine learning (ML) model predicting hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients after the first 5 years of entecavir (ETV) or tenofovir (TFV) therapy.

Robust multi-modal fusion architecture for medical data with knowledge distillation.

Computer methods and programs in biomedicine
BACKGROUND: The fusion of multi-modal data has been shown to significantly enhance the performance of deep learning models, particularly on medical data. However, missing modalities are common in medical data due to patient specificity, which poses a...

OptimCLM: Optimizing clinical language models for predicting patient outcomes via knowledge distillation, pruning and quantization.

International journal of medical informatics
BACKGROUND: Clinical Language Models (CLMs) possess the potential to reform traditional healthcare systems by aiding in clinical decision making and optimal resource utilization. They can enhance patient outcomes and help healthcare management throug...

Multimodal autism detection: Deep hybrid model with improved feature level fusion.

Computer methods and programs in biomedicine
OBJECTIVE: Social communication difficulties are a characteristic of autism spectrum disorder (ASD), a neurodevelopmental condition. The earlier method of diagnosing autism largely relied on error-prone behavioral observation of symptoms. More intell...

Deep representation learning of protein-protein interaction networks for enhanced pattern discovery.

Science advances
Protein-protein interaction (PPI) networks, where nodes represent proteins and edges depict myriad interactions among them, are fundamental to understanding the dynamics within biological systems. Despite their pivotal role in modern biology, reliabl...