AIMC Topic: Machine Learning

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Machine Learning Techniques for Personalized Detection of Epileptic Events in Clinical Video Recordings.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan i...
Monitoring, Physiologic Electroencephalography Seizures Video Recording Humans Machine Learning Intensive Care Units Precision Medicine Male Epilepsy
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Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
This study aimed at identifying the factors associated with neonatal mortality. We analyzed the Demographic and Health Survey (DHS) datasets from 10 Sub-Saharan countries. For each survey, we trained machine learning models to identify women who had ...
Female Infant, Newborn Africa South of the Sahara Humans Male Infant Mortality Machine Learning Infant Mothers Surveys and Questionnaires
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A Reliable Machine Learning Approach applied to Single-Cell Classification in Acute Myeloid Leukemia.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Machine Learning research applied to the medical field is increasing. However, few of the proposed approaches are actually deployed in clinical settings. One reason is that current methods may not be able to generalize on new unseen instances which d...
Reproducibility of Results Leukemia, Myeloid, Acute Single-Cell Analysis Humans Machine Learning
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VANTAGE6: an open source priVAcy preserviNg federaTed leArninG infrastructurE for Secure Insight eXchange.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Answering many of the research questions in the field of cancer informatics requires incorporating and centralizing data that are hosted by different parties. Federated Learning (FL) has emerged as a new approach in which a global model can be genera...
Privacy Learning Confidentiality Humans Machine Learning
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Neural Multi-Task Learning for Adverse Drug Reaction Extraction.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
A reliable and searchable knowledge database of adverse drug reactions (ADRs) is highly important and valuable for improving patient safety at the point of care. In this paper, we proposed a neural multi-task learning system, NeuroADR, to extract ADR...
Humans Machine Learning Data Mining Deep Learning Drug-Related Side Effects and Adverse Reactions Databases, Factual
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An Interpretable Machine Learning Survival Model for Predicting Long-term Kidney Outcomes in IgA Nephropathy.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
IgA nephropathy (IgAN) is common worldwide and has heterogeneous phenotypes. Predicting long-term outcomes is important for clinical decision-making. As right-censored patients become common during the long-term follow-up, either excluding these pati...
Humans Machine Learning Adult Middle Aged Prognosis Kidney Kidney Failure, Chronic Glomerulonephritis, IGA Disease Progression Cohort Studies
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Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
The efficacy of early fluid treatment in patients with sepsis is unclear and may contribute to serious adverse events due to fluid non-responsiveness. The current method of deciding if patients are responsive to fluid administration is often subjecti...
Fluid Therapy Machine Learning Male Sepsis Humans Middle Aged Logistic Models
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Automatically classifying the evidence type of drug-drug interaction research papers as a step toward computer supported evidence curation.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
A longstanding issue with knowledge bases that discuss drug-drug interactions (DDIs) is that they are inconsistent with one another. Computerized support might help experts be more objective in assessing DDI evidence. A requirement for such systems i...
Humans Machine Learning Drug Interactions Data Mining Pilot Projects Natural Language Processing Publications Computers Databases, Factual
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A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Medical ionizing radiation procedures and especially medical imaging are a non negligible source of exposure to patients. Whereas the biological effects of high absorbed doses are relatively well known, the effects of low absorbed doses are still deb...
Radiography Diagnostic Imaging Data Mining Databases, Factual Natural Language Processing Radiation Dosage Radiometry Database Management Systems Semantics Machine Learning Humans Documentation Terminology as Topic Algorithms
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Leveraging digital media data for pharmacovigilance.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
The development of novel drugs in response to changing clinical requirements is a complex and costly method with uncertain outcomes. Postmarket pharmacovigilance is essential as drugs often have under-reported side effects. This study intends to use ...
Drug-Related Side Effects and Adverse Reactions Diagnostic Tests, Routine Pharmacovigilance Machine Learning Social Media Internet Humans
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