AIMC Topic: Humans

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Machine learning prediction of STEMI incidence with SHAP interpretation of environmental determinants.

Scientific reports
ST-segment elevation myocardial infarction (STEMI) is a life-threatening cardiovascular event influenced by meteorological conditions and air pollution. Traditional statistical methods often fail to capture the complex, nonlinear relationships betwee...

English-focused CL-HAMC with contrastive learning and hierarchical attention for multiple-choice reading comprehension.

Scientific reports
Multiple-choice questions constitute a critical format for assessing language application proficiency in standardized English tests, such as BEC and TOEIC. Developing explanatory content for such materials traditionally relies heavily on manual labor...

Data-augmented machine learning for personalized carbohydrate-protein supplement recommendation for endurance.

Scientific reports
Carbohydrate-protein supplementation often improves endurance performance. However, effectiveness varies significantly among individuals due to unique personal characteristics. This study aimed to develop a predictive machine learning framework for p...

Graph attention networks-based prediction of MicroRNA-disease causality in head and neck neoplasms.

Scientific reports
Head and neck cancers represent a critical global health issue, contributing to substantial morbidity and mortality. Recent research has explored the role of microRNAs (miRNAs) in these cancers by constructing miRNA-associated disease networks using ...

Evaluation of VITA shade-based tooth color categories using deep learning.

Scientific reports
With the increasing interest in dental aesthetics, more patients are seeking tooth shade evaluations and whitening treatments. However, traditional methods of visually assessing tooth color with a commercial shade guide are often subjective, emphasiz...

Multi-texture synthesis through signal responsive neural cellular automata.

Scientific reports
Neural Cellular Automata have proven to be effective in various fields, with numerous biologically inspired applications. Particularly, neural cellular automata have been proven to be successful models for procedural generation of textures. They mode...

Automated meningioma detection using skull X ray images with deep learning and machine learning classifiers.

Scientific reports
This study aimed to develop a novel diagnostic tool for detecting meningioma using skull X-ray images, combining deep learning with traditional machine learning classifiers. The goal was to explore the potential of using a cost-effective and widely a...

Mitigating distributed denial of service-based cyberattack in federated computing framework using deep reinforcement learning with frilled lizard algorithm.

Scientific reports
A denial of service (DoS) attack is an essential and nonstop threat to cybersecurity. Generally, DoS attacks are executed by forcing a victim's computer to reset and consume its sources. Distributed DoS (DDoS) is the most underlined and significant a...

An intelligent brain tumor detection model using lightweight hybrid twin attentive pyramid convolutional network.

Scientific reports
Brain tumors (BTs) pose a serious threat to human health, and the optimized treatment and results depend on early and accurate detection. Although MRIs and other medical imaging technologies provide insightful information, it is still difficult to de...

LLMs outperform outsourced human coders on complex textual analysis.

Scientific reports
This paper evaluates the effectiveness of large language models (LLMs) in extracting complex information from text data. Using a corpus of Spanish news articles, we compare how accurately various LLMs and outsourced human coders reproduce expert anno...