AIMC Topic: False Negative Reactions

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Machine Learning Algorithms in Suicide Prevention: Clinician Interpretations as Barriers to Implementation.

The Journal of clinical psychiatry Apr 21, 2020
OBJECTIVE: Machine learning algorithms in electronic medical records can classify patients by suicide risk, but no research has explored clinicians' perceptions of suicide risk flags generated by these algorithms, which may affect algorithm implement...
False Negative Reactions False Positive Reactions Algorithms Health Personnel Physicians Electronic Health Records Female Adult Male Risk Assessment Attitude of Health Personnel Suicide Prevention Humans Machine Learning
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Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard.

Ophthalmology Mar 10, 2020
PURPOSE: To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss.
Retrospective Studies Female Aged Adult Sensitivity and Specificity Humans Glaucoma Artificial Intelligence Visual Acuity Vision Disorders Predictive Value of Tests Visual Fields False Negative Reactions Optic Nerve Diseases Cross-Sectional Studies Male Middle Aged Longitudinal Studies Monitoring, Physiologic
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Comparison of text processing methods in social media-based signal detection.

Pharmacoepidemiology and drug safety Aug 7, 2019
PURPOSE: Adverse event (AE) identification in social media (SM) can be performed using various types of natural language processing (NLP) and machine learning (ML). These methods can be categorized by complexity and precision level. Co-occurrence-bas...
Retrospective Studies Sensitivity and Specificity Social Media Natural Language Processing False Negative Reactions False Positive Reactions Adverse Drug Reaction Reporting Systems Feasibility Studies Drug-Related Side Effects and Adverse Reactions Data Collection Pharmacovigilance Datasets as Topic
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Prediction of early colorectal cancer metastasis by machine learning using digital slide images.

Computer methods and programs in biomedicine Jun 22, 2019
BACKGROUND AND OBJECTIVES: Prediction of lymph node metastasis (LNM) for early colorectal cancer (CRC) is critical for determining treatment strategies after endoscopic resection. Some histologic parameters for predicting LNM have been established, b...
Endoscopy Colorectal Neoplasms Male Middle Aged Lymph Nodes Algorithms Retrospective Studies Female Risk Factors Aged Keratins Lymphatic Metastasis Neoplasm Metastasis Immunohistochemistry False Negative Reactions False Positive Reactions Humans Machine Learning
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Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

International journal of radiation oncology, biology, physics May 31, 2019
PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radiation therapy physician orders.
Radiotherapy Dosage Organ Specificity Dose Fractionation, Radiation Radiologists Medical Errors Radiotherapy Planning, Computer-Assisted Radiotherapy Setup Errors Datasets as Topic Humans Technology, Radiologic Radiotherapy, Image-Guided Algorithms False Negative Reactions Neural Networks, Computer Simulation Training False Positive Reactions Neoplasms Cohort Studies ROC Curve Bayes Theorem
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Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.

European radiology Apr 16, 2019
PURPOSE: To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload.
ROC Curve Mass Screening Early Detection of Cancer Mammography Radiologists Workload Feasibility Studies Probability False Negative Reactions False Positive Reactions Humans Artificial Intelligence Female Breast Neoplasms
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Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs.

European radiology Apr 1, 2019
OBJECTIVE: To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). Hip fracture is a leading worldwide health problem for the elde...
Male Middle Aged Deep Learning ROC Curve Radiography, Abdominal Humans Feasibility Studies Aged Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Aged, 80 and over Hip Fractures Algorithms Young Adult False Negative Reactions Prognosis Adult Female Sensitivity and Specificity
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The use of artificial neural network analysis can improve the risk-stratification of patients presenting with suspected deep vein thrombosis.

British journal of haematology Feb 6, 2019
Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-existing hypothesis as to any associations that may exist. This technique has not previously been applied to the risk stratification of patients referre...
Female Fibrin Fibrinogen Degradation Products Adult Ultrasonography Male Humans Venous Thrombosis Middle Aged Neural Networks, Computer Predictive Value of Tests Risk Assessment Algorithms False Negative Reactions Biomarkers Proof of Concept Study Retrospective Studies
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Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination.

PloS one Dec 5, 2018
With the advance of next-generation sequencing (NGS) technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal b...
False Negative Reactions Humans Female False Positive Reactions Machine Learning Sequence Analysis, DNA Prenatal Diagnosis Young Adult Retrospective Studies Trisomy 13 Syndrome Diagnosis, Differential Pregnancy Adult Trisomy 18 Syndrome Genetic Testing Diagnosis, Computer-Assisted High-Throughput Nucleotide Sequencing Support Vector Machine Down Syndrome
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Determination of appropriate urine volume cutoff values for voided urine specimens to assess adequacy.

Journal of the American Society of Cytopathology Nov 7, 2018
INTRODUCTION: Incorporating urine volume into adequacy assessment was recommended by The Paris System for Reporting Urinary Cytology. The concept was relatively new, however, and supportive studies were sparse. We accordingly aimed to determine the r...
Urine Specimen Collection Logistic Models Humans Urologic Neoplasms Retrospective Studies Cytodiagnosis Female False Negative Reactions Aged Urine Male
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