AIMC Topic: False Positive Reactions

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Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques.

Computer methods and programs in biomedicine Jun 27, 2019
BACKGROUND: Diabetic patients treated with intensive insulin therapies require a tight glycemic control and may benefit from advanced tools to predict blood glucose (BG) concentration levels and hypo/hyperglycemia events. Prediction systems using mac...
Normal Distribution Insulin Infusion Systems Capillaries Bayes Theorem Hypoglycemia Postprandial Period Blood Glucose Self-Monitoring False Positive Reactions Retrospective Studies Female Reproducibility of Results Adult Sensitivity and Specificity Male Middle Aged Blood Glucose Insulin Diabetes Mellitus, Type 1 Hypoglycemic Agents Humans Machine Learning Algorithms Computer Simulation
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Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.

Computer methods and programs in biomedicine Jun 26, 2019
BACKGROUND AND OBJECTIVE: Wheezing is a common symptom of patients caused by asthma and chronic obstructive pulmonary diseases. Wheezing detection identifies wheezing lung sounds and helps physicians in diagnosis, monitoring, and treatment of pulmona...
Humans Machine Learning Sensitivity and Specificity Male Support Vector Machine Monitoring, Physiologic Models, Statistical Signal Processing, Computer-Assisted Software Algorithms Female Reproducibility of Results Adult Respiratory Sounds Telemedicine Artifacts Medical Informatics Pattern Recognition, Automated False Positive Reactions
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Neural networks versus Logistic regression for 30 days all-cause readmission prediction.

Scientific reports Jun 26, 2019
Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to the health...
Machine Learning Algorithms Female Aged Male Middle Aged Humans Neural Networks, Computer Area Under Curve Heart Failure Probability Patient Readmission False Positive Reactions Risk Deep Learning ROC Curve Logistic Models United States Predictive Value of Tests
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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...
False Negative Reactions False Positive Reactions Keratins Female Risk Factors Humans Aged Male Machine Learning Endoscopy Middle Aged Algorithms Colorectal Neoplasms Lymph Nodes Retrospective Studies Lymphatic Metastasis Neoplasm Metastasis Immunohistochemistry
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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.
Technology, Radiologic Neoplasms Cohort Studies Dose Fractionation, Radiation ROC Curve Bayes Theorem Radiotherapy, Image-Guided Radiologists Simulation Training Humans Radiotherapy Planning, Computer-Assisted Medical Errors Neural Networks, Computer Datasets as Topic Radiotherapy Setup Errors Algorithms False Negative Reactions False Positive Reactions Radiotherapy Dosage Organ Specificity
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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-...
Nonlinear Dynamics Computer Simulation False Positive Reactions Oligonucleotide Array Sequence Analysis Gene Expression Profiling Computational Biology Genetic Techniques Humans Area Under Curve Colonic Neoplasms Artificial Intelligence Machine Learning Software Algorithms
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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...
Humans False Positive Reactions Neural Networks, Computer Hair Algorithms Diagnosis, Computer-Assisted Databases, Factual Deep Learning Melanoma Image Processing, Computer-Assisted Skin Neoplasms Skin Reproducibility of Results Artifacts
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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.
Italy Registries False Positive Reactions Risk Middle Aged Support Vector Machine Models, Statistical Bayes Theorem Kidney Failure, Chronic Female Aged Humans Sensitivity and Specificity Male Machine Learning Cardiovascular Diseases Algorithms Databases, Factual Biomarkers Prognosis
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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.
False Negative Reactions False Positive Reactions Humans Artificial Intelligence Mammography Female Radiologists Breast Neoplasms Workload ROC Curve Feasibility Studies Mass Screening Probability Early Detection of Cancer
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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...
Humans Tomography, X-Ray Computed Sensitivity and Specificity Lung Image Processing, Computer-Assisted Lung Neoplasms Support Vector Machine False Positive Reactions
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