AIMC Topic: Algorithms

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Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease.

PloS one
This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Personalized Models and Differential Privacy (FLPMDP), for diagnosing arrhythmia from 12-lead electrocardiogram (ECG) signals. The architecture supports ...

FCRNet: Fast Fourier convolutional residual network for ventilator bearing fault diagnosis.

PloS one
This study presents FCRNet, a Fast Fourier Convolution Residual Network, tailored for fault diagnosis of mine ventilation bearings under complex operating conditions. By integrating residual learning with Fast Fourier Convolution (FFC), FCRNet employ...

Urine-based Raman markers for prostate cancer diagnosis: A machine learning approach using fingerprint and lipid spectral region.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study investigates the potential of Raman spectroscopy in distinguishing between healthy individuals and prostate cancer patients using urine samples. The Boruta algorithm was applied to Raman spectral data in two distinct wavenumber regions: 80...

StackPIP: An Effective Computational Framework for Accurate and Balanced Identification of Proinflammatory Peptides.

Journal of chemical information and modeling
Proinflammatory peptides (PIPs) play a crucial role in immune response modulation by orchestrating cytokine release and leukocyte recruitment. Accurate identification of PIPs is essential for understanding inflammation-related diseases and developing...

Temperature-Dependent Small-Molecule Solubility Prediction Using MoE-Enhanced Directed Message Passing Neural Networks.

Journal of chemical information and modeling
Solubility prediction is crucial for drug development and materials science, yet existing models struggle with generalizability across diverse solvents and temperatures. This study develops a novel solubility prediction model, DMPNN-MoE, which integr...

EDRMM: enhancing drug recommendation via multi-granularity and multi-attribute representation.

BMC bioinformatics
BACKGROUND: Drug recommendation is a crucial application of artificial intelligence in medical practice. Although many models have been proposed to solve this task, two challenges remain unresolved: (i) most existing models use all historical visits ...

FF Swin-Unet: a strategy for automated segmentation and severity scoring of NAFLD.

BMC medical imaging
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a significant risk factor for liver cancer and cardiovascular diseases, imposing substantial social and economic burdens. Computed tomography (CT) scans are crucial for diagnosing NAFLD and ass...

Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture.

Scientific reports
This paper presents a novel approach for personalized learning path generation by integrating deep knowledge tracing and cognitive load estimation within a unified framework. We propose a dual-stream neural network architecture that simultaneously mo...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Scientific reports
Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracerebral hemorrhage. We aimed to develop a risk assessment model to predict the risk of lower extremity DVT during hospitalization in patients with spontan...

Enhanced melanoma and non-melanoma skin cancer classification using a hybrid LSTM-CNN model.

Scientific reports
Melanoma is the most dangerous type of skin cancer. Although it accounts for only about 1% of all skin cancer cases, it is responsible for the majority of skin cancer-related deaths. Early detection and accurate diagnosis are crucial for improving th...