AIMC Topic: Machine Learning

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Evolutionary learning-derived lncRNA signature with biomarker discovery for predicting stage of colon adenocarcinoma.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
In recent years, long non-coding RNAs (lncRNAs) have emerged as potential regulators of biological processes and genes, with the potential to serve as valuable biomarkers for cancer diagnosis and prognosis prediction. This work proposes an evolutiona...
Algorithms Humans Adenocarcinoma Biomarkers, Tumor Machine Learning RNA, Long Noncoding Gene Expression Profiling Neoplasm Staging Colonic Neoplasms
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Physical, Social and Cognitive Stressor Identification using Electrocardiography-derived Features and Machine Learning from a Wearable Device.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Anxiety is a prevalent and detrimental mental health condition affecting young adults, particularly in college students who face a range of stressors including academic pressures, interpersonal relationships, and financial concerns. The ability to pr...
Young Adult Adult Male Machine Learning Signal Processing, Computer-Assisted Female Heart Rate Cognition Electrocardiography Humans Support Vector Machine Anxiety Stress, Psychological Wearable Electronic Devices
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Improving Neonatal Care with AI: Class Weight Optimization for Respiratory Distress Syndrome Prediction in Very Low Birth Weight Infants.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
In this study, we developed an AI model to predict Respiratory Distress Syndrome (RDS) in premature infants, aiming to reduce unnecessary treatment with artificial pulmonary surfactant. We analyzed data from 13,120 infants in 76 hospitals, considerin...
Machine Learning Algorithms Female Infant, Newborn Male Support Vector Machine Humans Neural Networks, Computer Artificial Intelligence Respiratory Distress Syndrome, Newborn Infant, Premature Infant, Very Low Birth Weight
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Leveraging Graph Neural Networks for MIC Prediction in Antimicrobial Resistance Studies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Antimicrobial resistance (AMR) poses a significant challenge in healthcare and public health, with organisms such as nontyphoidal Salmonella leading the way due to their escalating resistance to antimicrobial agents. This situation severely complicat...
Machine Learning Drug Resistance, Bacterial Humans Algorithms Microbial Sensitivity Tests Anti-Bacterial Agents Neural Networks, Computer Graph Neural Networks
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Explainable AI (XAI) for Neonatal Pain Assessment via Influence Function Modification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
As machine learning increasingly plays a crucial role in various medical applications, the need for improved explainability of these complex, often opaque models becomes more urgent. Influence functions have emerged as a critical method for explainin...
Algorithms Infant, Newborn Pain Measurement Humans Machine Learning
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Unsupervised Anomaly Detection by Learning Elastic Transformations Within an Autoencoder Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Machine learning has approached magnetic resonance image (MRI) analysis using multiple techniques, including deep supervised learning methodologies, where lesions such as tumors or features associated with defined pathologies have been identified sat...
Autoencoder Magnetic Resonance Imaging Unsupervised Machine Learning Humans Machine Learning Algorithms Brain Image Processing, Computer-Assisted
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High Throughput Phenotyping of Physician Notes with Large Language and Hybrid NLP Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Deep phenotyping is the detailed description of patient signs and symptoms using concepts from an ontology. The deep phenotyping of the numerous physician notes in electronic health records requires high throughput methods. Over the past 30 years, pr...
Humans Machine Learning Natural Language Processing Phenotype Physicians Electronic Health Records
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Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Deep learning models are being adopted and applied across various critical medical tasks, yet they are primarily trained to provide point predictions without providing degrees of confidence. Medical practitioner's trustworthiness of deep learning mod...
Humans Machine Learning Uncertainty Antineoplastic Agents Deep Learning Regression Analysis Algorithms Neoplasms
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Time-varying compartmental models with neural networks for pandemic infection forecasting.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The emergence and spread of deadly pandemics has repeatedly occurred throughout history, causing widespread infections and life loss. Forecasting the progression of pandemics is crucial for decision-makers to achieve its mitigation. This predictive t...
Time Factors Humans Neural Networks, Computer Forecasting Machine Learning SARS-CoV-2 Pandemics COVID-19
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Dynamic multi-hypergraph structure learning for disease diagnosis on multimodal data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
With its superior capability in complex data modeling, hypergraph computation is a powerful tool for many applications. In this work, we propose using hypergraph computation for disease prediction. Hypergraphs allow for the representation of higher-o...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Cluster Analysis Alzheimer Disease Machine Learning Algorithms Autism Spectrum Disorder
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