AIMC Topic: ROC Curve

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Is there a symptomatic distinction between the affective psychoses and schizophrenia? A machine learning approach.

Schizophrenia research Jul 24, 2018
Dubiety exists over whether clinical symptoms of schizophrenia can be distinguished from affective psychosis, the assumption being that absence of a "point of rarity" indicates lack of nosological distinction, based on prior group-level analyses. Adv...
Schizophrenic Psychology Affective Disorders, Psychotic Diagnosis, Computer-Assisted Adolescent Cohort Studies ROC Curve Schizophrenia Humans Young Adult Machine Learning Adult Female Male Aged Middle Aged
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Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Clinical cancer research : an official journal of the American Association for Cancer Research Jul 24, 2018
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...
Humans Prognosis Female Aged Stomach Neoplasms Biomarkers, Tumor Male Middle Aged Neoplasm Grading Survival Analysis Tumor Burden Immunohistochemistry ROC Curve Chemotherapy, Adjuvant Antineoplastic Combined Chemotherapy Protocols Treatment Outcome Support Vector Machine Neoplasm Staging
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Enhanced neonatal surgical site infection prediction model utilizing statistically and clinically significant variables in combination with a machine learning algorithm.

American journal of surgery Jul 24, 2018
BACKGROUND: Machine-learning can elucidate complex relationships/provide insight to important variables for large datasets. This study aimed to develop an accurate model to predict neonatal surgical site infections (SSI) using different statistical m...
Retrospective Studies Female Infant, Newborn Risk Factors Male Humans Machine Learning Surgical Wound Infection Algorithms Decision Support Techniques Risk Assessment Infant ROC Curve Logistic Models Area Under Curve
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A machine-learning framework for automatic reference-free quality assessment in MRI.

Magnetic resonance imaging Jul 21, 2018
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and th...
Magnetic Resonance Imaging Signal Processing, Computer-Assisted Humans Neural Networks, Computer Observer Variation Databases, Factual Fourier Analysis Prospective Studies Deep Learning Retrospective Studies ROC Curve Female Image Processing, Computer-Assisted Aged Support Vector Machine Adult Male Middle Aged
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On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

European journal of radiology Jul 20, 2018
PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic edema and non-contrast enhancing tumor is difficult as both appear hyperintense in T-W/FLAIR images. Most studies involving differentiation between vasog...
Middle Aged ROC Curve Image Processing, Computer-Assisted Glioma Aged Magnetic Resonance Imaging Humans Support Vector Machine Young Adult Diagnosis, Differential Brain Brain Edema Retrospective Studies Adult Postoperative Period Female Brain Neoplasms Preoperative Care Male
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Network-Based Drug Discovery: Coupling Network Pharmacology with Phenotypic Screening for Neuronal Excitability.

Journal of molecular biology Jul 18, 2018
Diseases such as chronic pain with complex etiologies are unlikely to respond to single, target-specific therapeutics but rather require intervention at multiple points within a perturbed disease system. Such approaches are being enabled by the rise ...
Neural Networks, Computer Drug Discovery ROC Curve Computational Biology Neurons High-Throughput Screening Assays Cell Culture Techniques Humans
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De novo profile generation based on sequence context specificity with the long short-term memory network.

BMC bioinformatics Jul 18, 2018
BACKGROUND: Long short-term memory (LSTM) is one of the most attractive deep learning methods to learn time series or contexts of input data. Increasing studies, including biological sequence analyses in bioinformatics, utilize this architecture. Ami...
Computational Biology Proteins Amino Acid Sequence Databases as Topic Sequence Homology, Amino Acid Neural Networks, Computer Deep Learning ROC Curve
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Osteoporosis detection in panoramic radiographs using a deep convolutional neural network-based computer-assisted diagnosis system: a preliminary study.

Dento maxillo facial radiology Jul 13, 2018
OBJECTIVES: To evaluate the diagnostic performance of a deep convolutional neural network (DCNN)-based computer-assisted diagnosis (CAD) system in the detection of osteoporosis on panoramic radiographs, through a comparison with diagnoses made by ora...
Diagnosis, Computer-Assisted Osteoporosis Humans Child Female Neural Networks, Computer Aged ROC Curve Adult Radiography, Panoramic Middle Aged
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Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning.

Scientific reports Jul 13, 2018
Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of p...
Humans Databases, Factual Female Young Adult Adult Datasets as Topic Stochastic Processes Rare Diseases Narcolepsy Polysomnography Male ROC Curve Data Interpretation, Statistical Models, Biological Supervised Machine Learning Sleep, REM Sleep Latency
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Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.

Annals of surgical oncology Jul 5, 2018
OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete response (rCR) is a poor predictor of pathologic complete response (pCR) of the axilla. We developed a convolutional neural network (CNN) algorithm to b...
Breast Neoplasms Biomarkers, Tumor Middle Aged ROC Curve Humans Receptor, ErbB-2 Neural Networks, Computer Neoadjuvant Therapy Carcinoma, Ductal, Breast Algorithms Follow-Up Studies Receptors, Estrogen Prognosis Magnetic Resonance Imaging Aged Antineoplastic Combined Chemotherapy Protocols Chemotherapy, Adjuvant Retrospective Studies Neoplasm Invasiveness Aged, 80 and over Carcinoma, Lobular Female Axilla Young Adult Adult Survival Rate
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