AIMC Topic: Machine Learning

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A combined strategy of feature selection and machine learning to identify predictors of prediabetes.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2020
OBJECTIVE: To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population.
Risk Factors Adult Male Middle Aged Machine Learning Algorithms Female Models, Theoretical Socioeconomic Factors Prevalence Area Under Curve Humans ROC Curve Prediabetic State Nutrition Surveys
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Temporal convolutional networks allow early prediction of events in critical care.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2020
OBJECTIVE: Clinical interventions and death in the intensive care unit (ICU) depend on complex patterns in patients' longitudinal data. We aim to anticipate these events earlier and more consistently so that staff can consider preemptive action.
Prognosis Intensive Care Units Female Hospitalization Neural Networks, Computer Machine Learning Computer Simulation Middle Aged Humans Aged Logistic Models Aged, 80 and over Critical Care Male Hospital Mortality
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Follow-Up on the Use of Machine Learning in Clinical Quality Assurance: Can We Detect Adverse Event Under-Reporting in Oncology Trials?

Drug safety Mar 1, 2020
Quality Assurance, Health Care Quality Indicators, Health Care Clinical Trials as Topic Adverse Drug Reaction Reporting Systems Neoplasms Antineoplastic Agents Drug-Related Side Effects and Adverse Reactions Research Report Humans Machine Learning Patient Safety
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Texture analysis and machine learning algorithms accurately predict histologic grade in small (< 4 cm) clear cell renal cell carcinomas: a pilot study.

Abdominal radiology (New York) Mar 1, 2020
PURPOSE: To predict the histologic grade of small clear cell renal cell carcinomas (ccRCCs) using texture analysis and machine learning algorithms.
Machine Learning Kidney Neoplasms Retrospective Studies Middle Aged Carcinoma, Renal Cell Tomography, X-Ray Computed Neoplasm Grading Pilot Projects Humans Female Radiographic Image Interpretation, Computer-Assisted Male
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Neuropsychiatric symptoms as predictors of conversion from MCI to dementia: a machine learning approach.

International psychogeriatrics Mar 1, 2020
OBJECTIVES: To use a Machine Learning (ML) approach to compare Neuropsychiatric Symptoms (NPS) in participants of a longitudinal study who developed dementia and those who did not.
Dementia Longitudinal Studies Neuropsychological Tests Delusions Behavioral Symptoms Anxiety Sleep Wake Disorders Depression Aggression Cognitive Dysfunction Male Middle Aged Disease Progression Humans Aged Machine Learning Aged, 80 and over Female
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Power and perils of prediction in palliative care.

Lancet (London, England) Feb 29, 2020
Humans Clinical Decision Rules Machine Learning Algorithms Palliative Care
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Towards Precision Medicine in Psychosis: Benefits and Challenges of Multimodal Multicenter Studies-PSYSCAN: Translating Neuroimaging Findings From Research into Clinical Practice.

Schizophrenia bulletin Feb 26, 2020
In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuro...
Research Design Precision Medicine Longitudinal Studies Neuroimaging Multicenter Studies as Topic Humans Psychotic Disorders Machine Learning
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Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia.

Schizophrenia bulletin Feb 26, 2020
Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. However, most previous studies have focused on single modalities only, ...
Humans Machine Learning Biomarkers Cerebral Cortex Connectome Nerve Net Basal Ganglia Thalamus Diffusion Tensor Imaging Middle Aged Magnetic Resonance Imaging Schizophrenia Neuroimaging Female Adult Male
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[Prognostic model of small sample critical diseases based on transfer learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2020
Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic models with poor performance of overfitting, large prediction error and instability, the long short-term memory transferring algorithm (transLSTM) was p...
Prognosis Models, Theoretical Disease Humans Machine Learning Algorithms
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Highly accurate and explainable detection of specimen mix-up using a machine learning model.

Clinical chemistry and laboratory medicine Feb 25, 2020
Background Delta check is widely used for detecting specimen mix-ups. Owing to the inadequate specificity and sparseness of the absolute incidence of mix-ups, the positive predictive value (PPV) of delta check is considerably low as it is labor consu...
Specimen Handling Humans Machine Learning Artifacts
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