AIMC Topic: Algorithms

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An integrated algorithm for single lead electrocardiogram signal analysis using deep learning with 12-lead data.

Scientific reports
Artificial intelligence (AI) algorithms have demonstrated remarkable efficiency in analyzing 12-lead clinical electrocardiogram (ECG) signals. This has sparked interest in leveraging cost-effective and user-friendly smart devices based on single-lead...

SHAP-driven insights into multimodal data: behavior phase prediction for industrial safety applications.

Scientific reports
Unsafe behaviors among coal miners are a primary factor contributing to accidents, posing significant challenges for safety management. This study develops a behavior state prediction framework using artificial intelligence and machine learning (ML) ...

Anston attentional network for structured data based stroke risk prediction in smart aging.

Scientific reports
To reduce the pressure on public health services caused by the aging population, nursing homes need to predict disease risks for the elderly periodically. To improve the disease risks predicting ability of nursing homes, we designed Anston (An Attent...

Optimizing imbalanced learning with genetic algorithm.

Scientific reports
Training AI models on imbalanced datasets with skewed class distributions poses a significant challenge, as it leads to model bias towards the majority class while neglecting the minority class. Various methods, such as Synthetic Minority Over Sampli...

Predicting drug-target affinity through triple pre-activated random residual planet convolution coupled attention network and contact maps.

Journal of computer-aided molecular design
Drug discovery relies on the ability to predict drug-target affinity (DTA), which allows for the efficient identification of drug candidates for certain protein targets. Scalability, accuracy, and interpretability are issues that traditional methods ...

Artificial intelligence-based algorithms for the diagnosis of retinopathy of prematurity.

The Cochrane database of systematic reviews
This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To assess the diagnostic performance of AI-based algorithms in comparison to the established reference standard of clinical diagnosis labels for ROP. Secondary obje...

MiThyCA: A Computational Pathology Pipeline for the Identification of Microscopic Foci of Papillary Thyroid Carcinoma-Like Nuclear Features with AI in Whole-Slide Histological Images.

Endocrine pathology
The histological identification of papillary thyroid carcinoma (PTC) is straightforward for experienced endocrine pathologists. The increase in radical thyroidectomies led to a raise in the rate of postoperative incidental subcentimeter PTC foci and ...

Tooth color prediction in intraoral images under different clinical lights using ML algorithms and CLAHE technique: an In-Vivo study.

Lasers in medical science
Tooth color selection is a crucial step in prosthetic dental treatments. However, the process often suffers from subjectivity, environmental light variability, and the high cost or lack of standardization in instrumental methods. This study aims to d...

CEAF: Capsule network enhanced feature fusion architecture for Chinese Named Entity Recognition.

PloS one
Chinese Named Entity Recognition (NER) is a fundamental task in the field of natural language processing, where achieving deep semantic mining of nested entities and accurate disambiguation of character-level boundary ambiguities stands as its core c...

Cardiovascular risk prediction and influencing predictors identification among Bangladeshi individuals using machine learning algorithms and association rule mining.

PloS one
BACKGROUND: Cardiovascular disease (CVD) encompasses a group of disorders that affect the heart and blood vessels, making it one of the leading causes of death globally, including in Bangladesh. Applying predictive modeling for the early identificati...