AIMC Topic: Algorithms

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M2OCNN: Many-to-One Collaboration Neural Networks for simultaneously multi-modal medical image synthesis and fusion.

Computer methods and programs in biomedicine Jan 28, 2025
BACKGROUND AND OBJECTIVE: Acquiring comprehensive information from multi-modal medical images remains a challenge in clinical diagnostics and treatment, due to complex inter-modal dependencies and missing modalities. While cross-modal medical image s...
Algorithms Image Processing, Computer-Assisted Multimodal Imaging Magnetic Resonance Imaging Humans Neural Networks, Computer
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Advancing lung cancer diagnosis: Combining 3D auto-encoders and attention mechanisms for CT scan analysis.

Journal of X-ray science and technology Jan 28, 2025
ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, se...
Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Lung Humans Tomography, X-Ray Computed Algorithms Sensitivity and Specificity Deep Learning Imaging, Three-Dimensional
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On QSPR analysis of glaucoma drugs using machine learning with XGBoost and regression models.

Computers in biology and medicine Jan 28, 2025
Glaucoma is an irreversible, progressive, degenerative eye disorder arising because of increased intraocular pressure, resulting in eventual vision loss if untreated. The QSPR relates, mathematically, by employing various algorithms, a specified prop...
Boosting Machine Learning Algorithms Humans Algorithms Quantitative Structure-Activity Relationship Glaucoma Machine Learning
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A multi-scale information fusion medical image segmentation network based on convolutional kernel coupled updata mechanism.

Computers in biology and medicine Jan 28, 2025
Medical image segmentation is pivotal in disease diagnosis and treatment. This paper presents a novel network architecture for medical image segmentation, termed TransDLNet, which is engineered to enhance the efficiency of multi-scale information uti...
Image Processing, Computer-Assisted Humans Algorithms Databases, Factual Neural Networks, Computer
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Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.

Computers in biology and medicine Jan 28, 2025
This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require careful anticoagulation management. With rising rates of diabetes and cardiovascular diseases, understanding the factors influencing warfarin therapy...
Machine Learning Algorithms Female Humans Middle Aged Diabetes Mellitus Anticoagulants Aged Male Warfarin Models, Biological
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Leveraging Network Target Theory for Efficient Prediction of Drug-Disease Interactions: A Transfer Learning Approach.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jan 28, 2025
Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with d...
Drug Discovery Deep Learning Humans Drug Interactions Algorithms
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Artificial-Intelligence Bio-Inspired Peptide for Salivary Detection of SARS-CoV-2 in Electrochemical Biosensor Integrated with Machine Learning Algorithms.

Biosensors Jan 28, 2025
Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical dev...
Saliva Algorithms Spike Glycoprotein, Coronavirus Machine Learning Peptides Molecular Docking Simulation Humans SARS-CoV-2 COVID-19 Electrochemical Techniques Biosensing Techniques Artificial Intelligence
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Integrating Machine Learning with MALDI-TOF Mass Spectrometry for Rapid and Accurate Antimicrobial Resistance Detection in Clinical Pathogens.

International journal of molecular sciences Jan 28, 2025
Antimicrobial resistance (AMR) is one of the most pressing public health challenges of the 21st century. This study aims to evaluate the efficacy of mass spectral data generated by VITEK MS instruments for predicting antibiotic resistance in , , and ...
Algorithms Anti-Bacterial Agents Microbial Sensitivity Tests Klebsiella pneumoniae Humans Drug Resistance, Bacterial Escherichia coli Machine Learning Staphylococcus aureus Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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Discovering patient groups in sequential electronic healthcare data using unsupervised representation learning.

BMC medical informatics and decision making Jan 28, 2025
INTRODUCTION: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Electronic Health Records Child Unsupervised Machine Learning Natural Language Processing Humans Cluster Analysis Algorithms
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Accuracy of artificial intelligence algorithms in predicting acute respiratory distress syndrome: a systematic review and meta-analysis.

BMC medical informatics and decision making Jan 28, 2025
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a serious threat to human life. Hence, early and accurate diagnosis and treatment are crucial for patient survival. This meta-analysis evaluates the accuracy of artificial intelligence in the ...
Algorithms Humans Sensitivity and Specificity Artificial Intelligence Respiratory Distress Syndrome
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