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False Positive Reactions

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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.
Bayes Theorem Radiologists Radiotherapy Planning, Computer-Assisted Datasets as Topic False Negative Reactions Algorithms Neoplasms Cohort Studies ROC Curve Radiotherapy, Image-Guided Simulation Training Medical Errors Radiotherapy Setup Errors Technology, Radiologic False Positive Reactions Radiotherapy Dosage Organ Specificity Dose Fractionation, Radiation Humans Neural Networks, Computer
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Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

PloS one May 23, 2019
BACKGROUND: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due to the large number of genes in human genome and the complex nature of biological networks. Most GS methods are not applicable to non-linear and multi-...
Area Under Curve Algorithms Oligonucleotide Array Sequence Analysis Humans Colonic Neoplasms Computer Simulation Artificial Intelligence Genetic Techniques Nonlinear Dynamics Gene Expression Profiling Machine Learning False Positive Reactions Computational Biology Software
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Digital hair segmentation using hybrid convolutional and recurrent neural networks architecture.

Computer methods and programs in biomedicine May 15, 2019
BACKGROUND AND OBJECTIVE: Skin melanoma is one of the major health problems in many countries. Dermatologists usually diagnose melanoma by visual inspection of moles. Digital hair removal can provide a non-invasive way to remove hair and hair-like re...
Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Skin Hair Artifacts Databases, Factual Humans False Positive Reactions Melanoma Neural Networks, Computer Skin Neoplasms Algorithms Reproducibility of Results
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A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

Computer methods and programs in biomedicine May 13, 2019
BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascular risk. This study aims at predicting, with a certain precision, death and cardiovascular diseases in dialysis patients.
Female Aged Sensitivity and Specificity Male Algorithms Databases, Factual Biomarkers Prognosis Bayes Theorem Kidney Failure, Chronic Italy Registries False Positive Reactions Cardiovascular Diseases Middle Aged Support Vector Machine Models, Statistical Humans Machine Learning Risk
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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.
Humans Feasibility Studies Probability False Negative Reactions False Positive Reactions Mass Screening Artificial Intelligence Mammography Early Detection of Cancer Female Radiologists Breast Neoplasms Workload ROC Curve
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Lungs nodule detection framework from computed tomography images using support vector machine.

Microscopy research and technique Apr 11, 2019
The emergence of cloud infrastructure has the potential to provide significant benefits in a variety of areas in the medical imaging field. The driving force behind the extensive use of cloud infrastructure for medical image processing is the exponen...
Lung Neoplasms Support Vector Machine False Positive Reactions Sensitivity and Specificity Humans Lung Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Journal of clinical monitoring and computing Apr 6, 2019
Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs monitors ranges from 0.72 to 0.99. We applied machine learning (ML) to ICU multi-sensor information to imitate a medical specialist in diagnosing pat...
Monitoring, Physiologic Knowledge Bases Critical Care Expert Systems Clinical Alarms Pattern Recognition, Automated False Positive Reactions Machine Learning Decision Support Techniques Retrospective Studies Intensive Care Units Humans
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Automated Segmentation of Colorectal Tumor in 3D MRI Using 3D Multiscale Densely Connected Convolutional Neural Network.

Journal of healthcare engineering Jan 31, 2019
The main goal of this work is to automatically segment colorectal tumors in 3D T2-weighted (T2w) MRI with reasonable accuracy. For such a purpose, a novel deep learning-based algorithm suited for volumetric colorectal tumor segmentation is proposed. ...
Contrast Media Magnetic Resonance Imaging False Positive Reactions Humans Colorectal Neoplasms Intestine, Large Neural Networks, Computer Deep Learning Algorithms Imaging, Three-Dimensional Image Processing, Computer-Assisted
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Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.

Biomedical engineering online Jan 22, 2019
BACKGROUND: A deep learning computer artificial intelligence system is helpful for early identification of ground glass opacities (GGOs).
Radiographic Image Interpretation, Computer-Assisted False Positive Reactions Image Processing, Computer-Assisted Lung Neoplasms Reproducibility of Results Solitary Pulmonary Nodule Radiology Sensitivity and Specificity Lung Diagnosis, Computer-Assisted Humans Deep Learning Algorithms Databases, Factual Tomography, X-Ray Computed
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An active learning framework for enhancing identification of non-artifactual intracranial pressure waveforms.

Physiological measurement Jan 18, 2019
OBJECTIVE: Intracranial pressure (ICP) is an important and established clinical measurement that is used in the management of severe acute brain injury. ICP waveforms are usually triphasic and are susceptible to artifact because of transient catheter...
Female Male Middle Aged Humans Intracranial Pressure Brain Injuries Artifacts Machine Learning Signal Processing, Computer-Assisted False Positive Reactions
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