AIMC Topic: Sensitivity and Specificity

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An FP's guide to AI-enabled clinical decision support.

The Journal of family practice Nov 1, 2019
To better understand the capabilities and challenges of artificial intelligence and machine learning, we look at the role they can play in screening for retinopathy and colon cancer.
Humans Neural Networks, Computer Colonoscopy Decision Support Systems, Clinical Early Detection of Cancer Colonic Neoplasms Retinal Diseases Artificial Intelligence Machine Learning Clinical Decision-Making Sensitivity and Specificity Family Practice
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Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

Metabolic syndrome and related disorders Nov 1, 2019
We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibr...
Non-alcoholic Fatty Liver Disease Liver Cirrhosis Hypertension Metabolic Syndrome Decision Making Adult Sensitivity and Specificity Cross-Sectional Studies Prognosis Male Retrospective Studies Female Prevalence Humans Aged Middle Aged Severity of Illness Index Machine Learning Disease Progression Diabetes Mellitus, Type 2 Algorithms
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A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

Critical care medicine Nov 1, 2019
OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.
Humans Machine Learning Algorithms Retrospective Studies Cohort Studies Decision Support Systems, Clinical Shock, Septic Text Messaging Hospitals, Teaching Electronic Health Records Sensitivity and Specificity Diagnosis, Computer-Assisted Sepsis
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[Classification of heart sound signals in congenital heart disease based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Oct 25, 2019
Cardiac auscultation is the basic way for primary diagnosis and screening of congenital heart disease(CHD). A new classification algorithm of CHD based on convolution neural network was proposed for analysis and classification of CHD heart sounds in ...
Heart Defects, Congenital Humans Heart Sounds Neural Networks, Computer Algorithms Sensitivity and Specificity
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Time-Independent Prediction of Burn Depth Using Deep Convolutional Neural Networks.

Journal of burn care & research : official publication of the American Burn Association Oct 16, 2019
We present in this paper the application of deep convolutional neural networks (CNNs), which is a state-of-the-art artificial intelligence (AI) approach in machine learning, for automated time-independent prediction of burn depth. Color images of fou...
Photography Sensitivity and Specificity Image Processing, Computer-Assisted Skin Burns Humans Neural Networks, Computer
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Computer-Aided Diagnosis of Pulmonary Fibrosis Using Deep Learning and CT Images.

Investigative radiology Oct 1, 2019
OBJECTIVES: The objective of this study is to assess the performance of a computer-aided diagnosis (CAD) system (INTACT system) for the automatic classification of high-resolution computed tomography images into 4 radiological diagnostic categories a...
Aged Aged, 80 and over Sensitivity and Specificity Male Diagnosis, Computer-Assisted Deep Learning Biopsy Middle Aged Lung Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Humans Algorithms Pulmonary Fibrosis Image Interpretation, Computer-Assisted
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The Use of Random Forests to Classify Amyloid Brain PET.

Clinical nuclear medicine Oct 1, 2019
PURPOSE: To evaluate random forests (RFs) as a supervised machine learning algorithm to classify amyloid brain PET as positive or negative for amyloid deposition and identify key regions of interest for stratification.
Neuroimaging Ethylene Glycols Male Middle Aged Cognitive Dysfunction Image Processing, Computer-Assisted Brain Aniline Compounds Female Humans Positron-Emission Tomography Aged Supervised Machine Learning Prospective Studies Amyloid Aged, 80 and over Alzheimer Disease Sensitivity and Specificity
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Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.

Journal of digital imaging Oct 1, 2019
We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemotherapy (NAC) response using a breast MRI tumor dataset prior to initiation of chemotherapy. An institutional review board-approved retrospective review o...
Image Interpretation, Computer-Assisted Datasets as Topic Treatment Outcome Magnetic Resonance Imaging Predictive Value of Tests Breast Humans Neural Networks, Computer Algorithms Sensitivity and Specificity Breast Neoplasms Deep Learning Retrospective Studies Female
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DL-CNV: A deep learning method for identifying copy number variations based on next generation target sequencing.

Mathematical biosciences and engineering : MBE Sep 30, 2019
Copy number variations (CNVs) play an important role in many types of cancer. With the rapid development of next generation sequencing (NGS) techniques, many methods for detecting CNVs of a single sample have emerged: (i) require genome-wide data of ...
Lung Neoplasms Sensitivity and Specificity Exons Receptor, ErbB-2 Deep Learning Carcinoma, Non-Small-Cell Lung Proto-Oncogene Proteins c-met Genome, Human Genome-Wide Association Study High-Throughput Nucleotide Sequencing DNA Copy Number Variations Humans ROC Curve False Positive Reactions Area Under Curve In Situ Hybridization, Fluorescence Algorithms Databases, Factual Reproducibility of Results
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Artificial Intelligence in Imaging: The Radiologist's Role.

Journal of the American College of Radiology : JACR Sep 1, 2019
Rapid technological advancements in artificial intelligence (AI) methods have fueled explosive growth in decision tools being marketed by a rapidly growing number of companies. AI developments are being driven largely by computer scientists, informat...
Practice Patterns, Physicians' Algorithms Humans Image Processing, Computer-Assisted Sensitivity and Specificity Radiology Artificial Intelligence Deep Learning Radiologists ROC Curve Role
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