AIMC Topic: Algorithms

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Real-Time Identification of Cricothyrotomy Landmarks in Emergency Care and Obstetric Patients Using Wireless Handheld Ultrasound and Edge-Computing Artificial Intelligence: A Prospective Observational Study.

Journal of medical systems
This study aimed to develop machine learning-based algorithms to assist physicians in ultrasound-guided localization of the cricoid cartilage (CC), thyroid cartilage (TC), and cricothyroid membrane (CTM) for cricothyroidotomy. Adult female participan...

A study of competitions in different fields through graphs under bipolar picture fuzzy environment.

PloS one
Recent developments in the theory of fuzzy graphs have led to many extensions for modeling real-world problems involving uncertainty. Among these, competition graphs are crucial for representing competitive and ecological systems. In this study, the ...

On the effectiveness of network metrics on key class prediction: An empirical study.

PloS one
Key classes are the most important classes in a software system, which provide an excellent foundation for developers-especially those new to the field-to understand unfamiliar software systems. In the past decade, several key class prediction (KCP) ...

Efficient Exploration of High-Dimensional Configuration Spaces for the Generation of Chemical Datasets.

Journal of chemical information and modeling
In this work, we introduce an automated methodology for the efficient and relatively inexpensive exploration of large high-dimensional chemical spaces, with particular focus on number-of-atoms-conserving processes, such as in mechanochemical reaction...

Large Language Models: A Paradigm Shift for Dementia Diagnosis and Care.

British journal of hospital medicine (London, England : 2005)
Dementia poses major challenges to healthcare worldwide. Traditional diagnostics rely on lengthy assessments, and access to specialist clinicians is limited. Large language models (LLMs), like Generative Pre-trained Transformer 4 (GPT-4) present new ...

Research on parallel computing of the olfactory neural network based on multithreading.

Scientific reports
To improve the computational efficiency of olfactory neural network, this paper proposes a multithreading-based parallel computing method. Firstly, focusing on the olfactory neural network and its neuronal equations, this paper analyzes and compares ...

A meta-learning framework to mitigate negative transfer in transfer learning applicable to drug design.

Scientific reports
Data sparseness is a major limiting factor for deep machine learning. In the natural sciences, data distributions are heterogeneous. For instance, in chemistry and early-phase drug discovery, compound and molecular property data are typically sparse ...

Advanced transformer with attention-based neural network framework for precise renal cell carcinoma detection using histological kidney images.

Scientific reports
Renal cell carcinoma (RCC) is one of the typical categories of kidney cancer and is a varied group of malignancies arising from epithelial cells of the kidney parenchyma. RCC has more than ten subtypes. Classification of RCC sub-types is mainly accor...

Adaptive heartbeat regulation using double deep reinforcement learning in a Markov decision process framework.

Scientific reports
The erratic nature of cardiac rhythms can precipitate a multitude of pathologies. Consequently, the endeavor to achieve stabilization of the human heartbeat has garnered significant scholarly interest in recent years. In this context, an adaptive non...

An intra- and inter-class context and consistency network for supervised and semi-supervised blastocyst segmentation.

Scientific reports
The implantation potential of an embryo is intricately linked to the quality of its blastocyst. Consequently, achieving an objective and precise identification of blastocyst morphology is imperative. The purpose of this study is to focus on the struc...