AIMC Topic: Machine Learning

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Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Clusters of differentiation () are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies () afford rich trans-disease repositioning opportunities. Within a ...
Antigens, CD20 Cell Adhesion Molecules Ki-1 Antigen Cell Differentiation Lupus Erythematosus, Systemic Reference Values Adult Sialic Acid Binding Ig-like Lectin 2 Female Humans Male Aged Machine Learning Middle Aged Young Adult Biomarkers Case-Control Studies Adolescent Child
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DrKnow: A Diagnostic Learning Tool with Feedback from Automated Clinical Decision Support.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Providing medical trainees with effective feedback is critical to the successful development of their diagnostic reasoning skills. We present the design of DrKnow, a web-based learning application that utilises a clinical decision support system (CDS...
Computer-Assisted Instruction Education, Medical, Undergraduate Simulation Training Teaching Students, Medical Feedback Decision Support Systems, Clinical Diagnosis, Differential Abdominal Pain Internet Humans Machine Learning
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Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring treatment to the individual patient is essential for the best outcomes. In this paper, we t...
Humans Machine Learning Sepsis Infusions, Intravenous Fluid Therapy Vasoconstrictor Agents Retrospective Studies Intensive Care Units Deep Learning Medical History Taking Observation
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Using Convolutional Neural Networks to Support Insertion of New Concepts into SNOMED CT.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Many major medical ontologies go through a regular (bi-annual, monthly, etc.) release cycle. A new release will contain corrections to the previous release, as well as genuinely new concepts that are the result of either user requests or new developm...
Support Vector Machine Systematized Nomenclature of Medicine Neural Networks, Computer Machine Learning
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Investigating a Needle-Based Epidural Procedure in Obstetric Anesthesia.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
This study investigates the safety and efficacy of a large-dose, needle-based epidural technique in obstetric anesthesia. The technique differs from a standard, catheter-based approach in that the anesthetic dose is administered through an epidural n...
Anesthesia, Obstetrical Anesthesia, Epidural Needles Task Performance and Analysis Humans Machine Learning Workflow Analgesia, Obstetrical Hypotension Pregnancy Female Anesthetics, Local
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Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A better EMR would provide concise, context sensitive patient data, but doing so entails the difficult task of knowing which data are relevant. To determin...
Humans Diagnostic Tests, Routine Machine Learning Information Seeking Behavior Electronic Health Records Medical Records Systems, Computerized User-Computer Interface Respiratory Insufficiency Physicians Acute Kidney Injury Intensive Care Units
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Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Text de-identification is an application of clinical natural language processing that offers significant efficiency and scalability advantages. Hence, various learning algorithms have been applied to this task to yield better performance. Instead of ...
Natural Language Processing Data Anonymization Methods Machine Learning Humans Algorithms Electronic Health Records
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A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
As the cost of DNA sequencing continues to fall, an increasing amount of information on human genetic variation is being produced that could help progress precision medicine. However, information about such mutations is typically first made available...
Mutation Data Mining DNA Mutational Analysis Humans Deep Learning Databases, Genetic Machine Learning
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Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Recent studies documented the importance of individuality and heterogeneity in care planning. In practice, varying behavioral responses are revealed in patients' care management (CM) records. However, today's care programs are structured around popul...
Humans Machine Learning Precision Medicine Medical Records Decision Making Patient Care Planning Behavior Patient Care Management Patient-Centered Care Datasets as Topic
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Phenotyping through Semi-Supervised Tensor Factorization (PSST).

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
A computational phenotype is a set of clinically relevant and interesting characteristics that describe patients with a given condition. Various machine learning methods have been proposed to derive phenotypes in an automatic, high-throughput manner....
Hypertension Electronic Health Records Diabetes Mellitus, Type 2 Computational Biology Algorithms Humans Phenotype Machine Learning
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