AIMC Topic: Algorithms

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Development and interpretation of a machine learning risk prediction model for post-stroke depression in a Chinese population.

Scientific reports
Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learning (ML) remains limited. The aim of this study is to develop a superior predictive model based on ML algorithms for PSD in the Chinese population. We r...

YOLO-LeafNet: a robust deep learning framework for multispecies plant disease detection with data augmentation.

Scientific reports
Plant diseases significantly harm crops, resulting in significant economic losses across the globe. In order to reduce the harm that these diseases produce, plant diseases must be diagnosed accurately and timely manner. In this work, a YOLO-LeafNet a...

Daily insider threat detection with hybrid TCN transformer architecture.

Scientific reports
Internal threats are becoming more common in today's cybersecurity landscape. This is mainly because internal personnel often have privileged access, which can be exploited for malicious purposes. Traditional detection methods frequently fail due to ...

Transfer learning driven fake news detection and classification using large language models.

Scientific reports
Today, the problem of using social media to spread false information is not only widespread but also quite serious. The extensive dissemination of fake news, regardless of whether it is produced by human beings or computer programs, has a negative im...

Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study.

Virology journal
Antiretroviral therapy (ART) has transformed HIV from a rapidly progressive and fatal disease to a chronic disease with limited impact on life expectancy. However, people living with HIV(PLWHs) faced high critical illness risk due to the increased pr...

Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images.

Scientific reports
Kidney cancer is a leading cause of cancer-related mortality, with renal cell carcinoma (RCC) being the most prevalent form, accounting for 80-85% of all renal tumors. Traditional diagnosis of kidney cancer requires manual examination and analysis of...

A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis.

Scientific reports
Speech is one of the most efficient methods of communication among humans, inspiring advancements in machine speech processing under Natural Language Processing (NLP). This field aims to enable computers to analyze, comprehend, and generate human lan...

Machine learning enables legal risk assessment in internet healthcare using HIPAA data.

Scientific reports
This study explores how artificial intelligence technologies can enhance the regulatory capacity for legal risks in internet healthcare based on a machine learning (ML) analytical framework and utilizes data from the health insurance portability and ...

AI-driven framework for automated detection of kidney stones in CT images: integration of deep learning architectures and transformers.

Biomedical physics & engineering express
. Kidney stones, a prevalent urological condition, associated with acute pain requires prompt and precise diagnosis for optimal therapeutic intervention. While computed tomography (CT) imaging remains the definitive diagnostic modality, manual interp...

A lightweight hybrid DL model for multi-class chest x-ray classification for pulmonary diseases.

Biomedical physics & engineering express
Pulmonary diseases have become one of the main reasons for people's health decline, impacting millions of people worldwide. Rapid advancement of deep learning has significantly impacted medical image analysis by improving diagnostic accuracy and effi...