AIMC Topic: Machine Learning

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Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework.

IEEE journal of biomedical and health informatics Feb 10, 2025
High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for localizing the seizure onset zone (SOZ) in patients with focal refractory epilepsy. Despite their clinical significance, HFO analysis is often compro...
Electrocorticography Adult Male Electroencephalography Brain Humans Signal Processing, Computer-Assisted Female Artifacts Machine Learning Young Adult Epilepsies, Partial Algorithms
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Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

IEEE journal of biomedical and health informatics Feb 10, 2025
Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk individuals, determining treatment needs, monitoring prevention and intervention efforts, and recruit...
Electronic Health Records Female Young Adult Prevalence Humans Insurance Claim Review Adult Opioid-Related Disorders Machine Learning Male Middle Aged
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Prediction of the Extent of Blood-Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model.

Pharmaceutical research Feb 10, 2025
INTRODUCTION: The unbound brain-to-plasma partition coefficient (K) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling. K values for specific compounds ar...
Models, Biological Biological Transport Central Nervous System Agents Quantitative Structure-Activity Relationship Animals Rats Pharmaceutical Preparations Algorithms Machine Learning Brain Blood-Brain Barrier
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Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.

Circulation. Arrhythmia and electrophysiology Feb 10, 2025
BACKGROUND: It is difficult to identify patients with atrial fibrillation (AF) most likely to respond to ablation. While any arrhythmia patient may recur after acutely successful ablation, AF is unusual in that patients may have long-term arrhythmia ...
Electrophysiologic Techniques, Cardiac Machine Learning Treatment Outcome Phenotype Action Potentials Humans Middle Aged Heart Rate Predictive Value of Tests Time Factors Catheter Ablation Female Registries Electrocardiography Aged Atrial Fibrillation Male
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Machine Learning Identification and Classification of Mitosis and Migration of Cancer Cells in a Lab-on-CMOS Capacitance Sensing Platform.

IEEE journal of biomedical and health informatics Feb 10, 2025
Cell culture assays play a vital role in various fields of biology. Conventional assay techniques like immunohistochemistry, immunofluorescence, and flow cytometry offer valuable insights into cell phenotype and behavior. However, each of these techn...
Lab-On-A-Chip Devices Mitosis Electric Capacitance Cell Line, Tumor Single-Cell Analysis Cell Movement Humans Machine Learning
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Incremental Classification for High-Dimensional EEG Manifold Representation Using Bidirectional Dimensionality Reduction and Prototype Learning.

IEEE journal of biomedical and health informatics Feb 10, 2025
In brain-computer interface (BCI) systems, symmetric positive definite (SPD) manifold within Riemannian space has been frequently utilized to extract spatial features from electroencephalogram (EEG) signals. However, the intrinsic high dimensionality...
Principal Component Analysis Electroencephalography Signal Processing, Computer-Assisted Algorithms Brain Adult Brain-Computer Interfaces Dimensionality Reduction Humans Neural Networks, Computer Machine Learning
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ADR-DQPU: A Novel ADR Signal Detection Using Deep Reinforcement and Positive-Unlabeled Learning.

IEEE journal of biomedical and health informatics Feb 10, 2025
The medical community has grappled with the challenge of analysis and early detection of severe and unknown adverse drug reactions (ADRs) from Spontaneous Reporting Systems (SRSs) like the FDA Adverse Event Reporting System (FAERS), which often lack ...
Machine Learning Algorithms Deep Learning Drug-Related Side Effects and Adverse Reactions Humans Adverse Drug Reaction Reporting Systems
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EEG Temporal-Spatial Feature Learning for Automated Selection of Stimulus Parameters in Electroconvulsive Therapy.

IEEE journal of biomedical and health informatics Feb 10, 2025
The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be high if an excessive stimulus is applied to induce the necessary generalized seizure (GS); Conversely, inadequate stimulus results in failure. Recent...
Middle Aged Electroencephalography Humans Female Seizures Adult Machine Learning Signal Processing, Computer-Assisted Male Electroconvulsive Therapy
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Partial Annotation Learning for Biomedical Entity Recognition.

IEEE journal of biomedical and health informatics Feb 10, 2025
Named Entity Recognition (NER) is a key task to support biomedical research. In Biomedical Named Entity Recognition (BioNER), obtaining high-quality expert annotated data is laborious and expensive, leading to the development of automatic approaches ...
Data Mining Data Curation Databases, Factual Biomedical Research Natural Language Processing Humans Machine Learning
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Predicting Clinical Anticancer Drug Response of Patients by Using Domain Alignment and Prototypical Learning.

IEEE journal of biomedical and health informatics Feb 10, 2025
Anticancer drug response prediction is crucial in developing personalized treatment plans for cancer patients. However, High-quality patient anticancer drug response data are scarce and cell line data and patient data have different distributions, mo...
Humans Neoplasms Antineoplastic Agents Cell Line, Tumor Machine Learning Computational Biology Databases, Factual Precision Medicine
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