AIMC Topic: Incidence

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External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules.

Thorax Mar 5, 2020
BACKGROUND: Estimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI...
Neural Networks, Computer Artificial Intelligence Algorithms Databases, Factual Prognosis Humans Middle Aged Risk Assessment Incidence Cohort Studies ROC Curve Lung Neoplasms Retrospective Studies Female Aged Adult Male Multiple Pulmonary Nodules Early Detection of Cancer Neoplasm Invasiveness Predictive Value of Tests Neoplasm Staging Area Under Curve Cell Transformation, Neoplastic
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An AI-based approach in determining the effect of meteorological factors on incidence of malaria.

Frontiers in bioscience (Landmark edition) Mar 1, 2020
This study presents the classification of malaria-prone zones based on (a) meteorological factors, (b) demographics and (c) patient information. Observations are performed on extended features in dataset over the spiking and non-spiking classifiers i...
Humans India Neural Networks, Computer Algorithms Models, Theoretical Malaria Reproducibility of Results Support Vector Machine Animals Insect Vectors Incidence Meteorological Concepts
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Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Feb 25, 2020
BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel ...
Genetic Heterogeneity Utah Pedigree Female Neoplastic Syndromes, Hereditary Humans Risk Factors Incidence Machine Learning Aged Adult Genetic Predisposition to Disease Aged, 80 and over Databases, Factual Male Urinary Bladder Neoplasms Young Adult Middle Aged Data Mining Risk Assessment Data Collection Adolescent
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Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

The lancet. Gastroenterology & hepatology Jan 22, 2020
BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system...
Clinical Alarms Colorectal Neoplasms Adenoma Male Diagnosis, Computer-Assisted Double-Blind Method Middle Aged Deep Learning Colonic Polyps Colonoscopy Humans China Observer Variation Case-Control Studies Incidence Female Early Diagnosis Adult Mass Screening
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Forecast of Dengue Cases in 20 Chinese Cities Based on the Deep Learning Method.

International journal of environmental research and public health Jan 10, 2020
Dengue fever (DF) is one of the most rapidly spreading diseases in the world, and accurate forecasts of dengue in a timely manner might help local government implement effective control measures. To obtain the accurate forecasting of DF cases, it is ...
Disease Outbreaks Deep Learning Incidence Cities Dengue Humans Neural Networks, Computer Forecasting
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A reliable time-series method for predicting arthritic disease outcomes: New step from regression toward a nonlinear artificial intelligence method.

Computer methods and programs in biomedicine Jan 9, 2020
BACKGROUND AND OBJECTIVE: The interrupted time-series (ITS) concept is performed using linear regression to evaluate the impact of policy changes in public health at a specific time. Objectives of this study were to verify, with an artificial intelli...
Humans Artificial Intelligence Research Design Incidence Arthritis, Rheumatoid Outcome Assessment, Health Care Arthroplasty, Replacement, Knee Linear Models Arthroplasty, Replacement, Hip Hip Knee Interrupted Time Series Analysis
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Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes.

Journal of critical care Jan 9, 2020
PURPOSE: Identification of patients for epidemiologic research through administrative coding has important limitations. We investigated the feasibility of a search based on natural language processing (NLP) on the text sections of electronic health r...
Hospitalization Young Adult Databases, Factual False Positive Reactions Adult Natural Language Processing Prospective Studies International Classification of Diseases Sensitivity and Specificity Epidemiologic Studies Humans Incidence Intensive Care Units Middle Aged Pattern Recognition, Automated Software Electronic Health Records Shock, Septic Female Predictive Value of Tests
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A new backpropagation neural network classification model for prediction of incidence of malaria.

Frontiers in bioscience (Landmark edition) Jan 1, 2020
Malaria is an infectious disease caused by parasitic protozoans of the Plasmodium family. These parasites are transmitted by mosquitos which are common in certain parts of the world. Based on their specific climates, these regions have been classifie...
Seasons Humidity Geography Rain Humans Neural Networks, Computer Algorithms Temperature Reproducibility of Results Incidence India Models, Theoretical Support Vector Machine Malaria
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Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer.

International journal of medical informatics Dec 28, 2019
BACKGROUND: The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual treatment-decision making. However, this remains a challenge even for experienced multidisciplinary cent...
Mouth Neoplasms Neoplasm Recurrence, Local Combined Modality Therapy Female Supervised Machine Learning Chemoradiotherapy Cohort Studies Aged Humans Male Tongue Neoplasms Child Algorithms Finland Support Vector Machine Prognosis Decision Trees Bayes Theorem Aged, 80 and over Young Adult Adult Middle Aged Brazil Adolescent Incidence
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A novel model for malaria prediction based on ensemble algorithms.

PloS one Dec 26, 2019
BACKGROUND AND OBJECTIVE: Most previous studies adopted single traditional time series models to predict incidences of malaria. A single model cannot effectively capture all the properties of the data structure. However, a stacking architecture can s...
Incidence Humans Malaria Algorithms Communicable Diseases Deep Learning China
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