AIMC Topic: Area Under Curve

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Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
Software Female Skin Neoplasms Aged Aged, 80 and over Humans Lentigo Area Under Curve Biopsy Skin Datasets as Topic False Positive Reactions Photography Keratosis, Seborrheic Warts Granuloma, Pyogenic Keratosis, Actinic Young Adult Deep Learning Adult ROC Curve Male Image Processing, Computer-Assisted Middle Aged Diagnosis, Differential Predictive Value of Tests
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Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

BMC bioinformatics Feb 6, 2018
BACKGROUND: The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been ...
Amino Acids Binding Sites Protein Interaction Domains and Motifs ROC Curve Support Vector Machine Proteins Area Under Curve
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Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Academic radiology Feb 1, 2018
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction.
Humans Neural Networks, Computer ROC Curve Mammography Retrospective Studies Area Under Curve Breast Parenchymal Tissue Female Adult Breast Neoplasms Case-Control Studies
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Machine Learning on a Genome-wide Association Study to Predict Late Genitourinary Toxicity After Prostate Radiation Therapy.

International journal of radiation oncology, biology, physics Jan 31, 2018
PURPOSE: Late genitourinary (GU) toxicity after radiation therapy limits the quality of life of prostate cancer survivors; however, efforts to explain GU toxicity using patient and dose information have remained unsuccessful. We identified patients w...
Predictive Value of Tests Area Under Curve Urinary Retention Quality of Life Humans Genotyping Techniques Prostatic Neoplasms Genome-Wide Association Study Urination Machine Learning Brachytherapy Androgen Antagonists Polymorphism, Single Nucleotide Symptom Assessment Reproducibility of Results Urination Disorders Confidence Intervals Regression Analysis Male Urogenital System Risk Nocturia Lower Urinary Tract Symptoms
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Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.

Radiology Jan 30, 2018
Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were ob...
Electronic Health Records Humans Sensitivity and Specificity Natural Language Processing Machine Learning Area Under Curve Databases, Factual Tomography, X-Ray Computed Radiology
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Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Jan 30, 2018
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or si...
Reproducibility of Results Humans Sequence Analysis, Protein ROC Curve Machine Learning Protein Binding Software Quercetin Receptors, G-Protein-Coupled Algorithms Area Under Curve Ligands False Positive Reactions Binding Sites Amino Acid Motifs
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Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.

BMJ open Jan 26, 2018
OBJECTIVES: We validate a machine learning-based sepsis-prediction algorithm () for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate robustness to missing data, customisation to site-specifi...
Humans Machine Learning Algorithms Databases, Factual Prognosis Retrospective Studies Intensive Care Units Female Aged Shock, Septic Young Adult Area Under Curve Emergency Service, Hospital Vital Signs Length of Stay Adult San Francisco Boston Sepsis Adolescent Hospital Mortality ROC Curve Male Middle Aged Severity of Illness Index Patients' Rooms
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Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network.

PloS one Jan 19, 2018
Although there have been reports of the successful diagnosis of skin disorders using deep learning, unrealistically large clinical image datasets are required for artificial intelligence (AI) training. We created datasets of standardized nail images ...
Diagnosis, Computer-Assisted Area Under Curve Dermatologists Image Interpretation, Computer-Assisted Foot Dermatoses Hand Dermatoses Onychomycosis Aged Young Adult Adult Male Middle Aged Machine Learning Algorithms Databases, Factual Humans Female Neural Networks, Computer Artificial Intelligence
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A method of gene expression data transfer from cell lines to cancer patients for machine-learning prediction of drug efficiency.

Cell cycle (Georgetown, Tex.) Jan 17, 2018
Personalized medicine implies that distinct treatment methods are prescribed to individual patients according several features that may be obtained from, e.g., gene expression profile. The majority of machine learning methods suffer from the deficien...
Humans Machine Learning Databases, Factual Precision Medicine Antineoplastic Agents ROC Curve Gene Expression Regulation, Neoplastic Area Under Curve Kidney Neoplasms
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Revealing Alzheimer's disease genes spectrum in the whole-genome by machine learning.

BMC neurology Jan 10, 2018
BACKGROUND: Alzheimer's disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes i...
Genome-Wide Association Study ROC Curve Area Under Curve Alzheimer Disease Humans Machine Learning Sensitivity and Specificity
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