AIMC Topic: Algorithms

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Multi-branch convolutional neural network with cross-attention mechanism for emotion recognition.

Scientific reports
Research on emotion recognition is an interesting area because of its wide-ranging applications in education, marketing, and medical fields. This study proposes a multi-branch convolutional neural network model based on cross-attention mechanism (MCN...

Detection of sleep apnea using only inertial measurement unit signals from apple watch: a pilot-study with machine learning approach.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Despite increased awareness of sleep hygiene, over 80% of sleep apnea cases remain undiagnosed, underscoring the need for accessible screening methods. This study presents a method for detecting sleep apnea using data from the Apple Watch's ...

HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease.

Journal of translational medicine
BACKGROUND: The traditional process of developing new drugs is time-consuming and often unsuccessful, making drug repurposing an appealing alternative due to its speed and safety. Graph neural networks (GCNs) have emerged as a leading approach for pr...

Integrating machine learning for treatment decisions in anterior open bite orthodontic cases: A retrospective study.

Journal of the World federation of orthodontists
INTRODUCTION: This article explores the integration of machine learning (ML) algorithms to aid in treatment planning and extraction decisions for anterior open bite cases, leveraging demographic, clinical, and radiographic data to predict treatment o...

A continuous-action deep reinforcement learning-based agent for coronary artery centerline extraction in coronary CT angiography images.

Medical & biological engineering & computing
The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based...

Smart home-assisted anomaly detection system for older adults: a deep learning approach with a comprehensive set of daily activities.

Medical & biological engineering & computing
Smart homes have the potential to enable remote monitoring of the health and well-being of older adults, leading to improved health outcomes and increased independence. However, current approaches only consider a limited set of daily activities and d...

Optimizing Skin Cancer Diagnosis: A Modified Ensemble Convolutional Neural Network for Classification.

Microscopy research and technique
Skin cancer is recognized as one of the most harmful cancers worldwide. Early detection of this cancer is an effective measure for treating the disease efficiently. Traditional skin cancer detection methods face scalability challenges and overfitting...

A prompt tuning method based on relation graphs for few-shot relation extraction.

Neural networks : the official journal of the International Neural Network Society
Prompt-tuning has recently proven effective in addressing few-shot tasks. However, task resources remain severely limited in the specific domain of few-shot relation extraction. Despite its successes, prompt-tuning faces challenges distinguishing bet...

Machine Learning-Powered Optimization of a CHO Cell Cultivation Process.

Biotechnology and bioengineering
Chinese Hamster Ovary (CHO) cells are the most widely used cell lines to produce recombinant therapeutic proteins such as monoclonal antibodies (mAbs). However, the optimization of the CHO cell culture process is very complex and influenced by variou...

Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries.

Computer methods and programs in biomedicine
PURPOSE: In medical deep learning, models not trained from scratch are typically fine-tuned based on ImageNet-pretrained models. We posit that pretraining on data from the domain of the downstream task should almost always be preferable.