AIMC Topic: Algorithms

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Automatic differentiation of voluntary and tremulous motion using ensemble empirical mode decomposition and convolutional Bi-directional LSTM.

Scientific reports
To develop applications for assisting Parkinson's disease (PD) patients, extracting Parkinsonian tremors from the raw signal is crucial; however, conventional methods such as filtering require a preset frequency range, and a poorly set frequency rang...

Revisiting Challenges in Real-world Video Colonoscopy using End-to-End Two Stream Polyp Detection Transformer (TS-PDTR).

Journal of medical systems
Accurate polyp detection is essential for the early diagnosis and effective treatment of colorectal cancer (CRC). However, colonoscopy videos in real-world clinical settings present significant challenges, often causing existing algorithms to fail. C...

Optimized hybrid RNN-GRU model for predictive diagnosis of cardiovascular disease.

Biomedical physics & engineering express
Cardiovascular disease (CVD) continues to be the leading cause of death for individuals all over the globe, and India bears a disproportionate share of the burden associated with this condition. A hybrid deep learning model that combines Recurrent Ne...

Early warning of regime switching in a financial time series: A heteroskedastic network model.

PloS one
Regime switching in a time series is an important and challenging issue in complex financial system analysis. Existing regime models have focused on the features of fluctuations at a single point in financial time series, often neglecting time series...

Construction and application of machine learning models for predicting intradialytic hypotension.

PloS one
INTRODUCTION: Intradialytic hypotension (IDH) remains a prevalent complication of hemodialysis, which is associated with adverse outcomes for patients. This study seeks to harness machine learning to construct predictive models for IDH based on multi...

Gait recognition using spatio-temporal representation fusion learning network with IMU-based skeleton graph and body partition strategy.

PloS one
The precise recognition of human lower limb movements based on wearable sensors is very important for human-computer interaction. However, the existing methods tend to ignore the dynamic spatial information in the process of executing human lower lim...

BLSAM-TIP: Improved and robust identification of tyrosinase inhibitory peptides by integrating bidirectional LSTM with self-attention mechanism.

PloS one
Tyrosinase plays a central role in melanin biosynthesis, and its dysregulation has been implicated in the pathogenesis of various pigmentation disorders. The precise identification of tyrosinase inhibitory peptides (TIPs) is critical, as these bioact...

Optimization of machine tool processing scheduling based on differential evolution algorithm.

PloS one
Machine tool processing scheduling plays a pivotal role in modern manufacturing systems, significantly influencing production efficiency, resource utilization, and timely delivery. Due to its combinatorial and NP-hard characteristics, traditional opt...

Deep intelligence: a four-stage deep network for accurate brain tumor segmentation.

Scientific reports
Image segmentation is an essential research field in image processing that has developed from traditional processing techniques to modern deep learning methods. In medical image processing, the primary goal of the segmentation process is to segment o...

Age estimation of children and adolescents from mandibles using machine learning.

Scientific reports
Age estimation is a crucial step in forensic identification, particularly in scenarios where dental structures may be absent. This study aimed to develop and evaluate supervised machine learning models to predict chronological age based on mandibular...