Machine learning for medical diagnosis: history, state of the art and perspective
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Distributed classifier based on genetically engineered bacterial cell culturesBPLT+: a Bayesian-based personalized recommendation model for health careCombination of single quantitative parameters into multiparametric model for ischemia detection is not superior to visual assessment during dobutamine stress echocardiography.Glaucoma Diagnostic Accuracy of Machine Learning Classifiers Using Retinal Nerve Fiber Layer and Optic Nerve Data from SD-OCT.Learning from data: recognizing glaucomatous defect patterns and detecting progression from visual field measurementsMachine learning and systems genomics approaches for multi-omics data.Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.Rapid evaluation of human biomonitoring data using pattern recognition systems.Machine learning and radiology.Bayesian networks for clinical decision support in lung cancer care.Machine learning applications in cancer prognosis and predictionA comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRIMachine learning approach to extract diagnostic and prognostic thresholds: application in prognosis of cardiovascular mortalityClinical and statistical correlation of various lumbar pathological conditions.Neuropsychological test selection for cognitive impairment classification: A machine learning approachLongitudinal histories as predictors of future diagnoses of domestic abuse: modelling study.Optimizing Neuropsychological Assessments for Cognitive, Behavioral, and Functional Impairment Classification: A Machine Learning StudyPredicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project.Radiomic analysis of soft tissues sarcomas can distinguish intermediate from high-grade lesions.Machine Learning for Medical Imaging.Research Review: Multi-informant integration in child and adolescent psychopathology diagnosis.Machine Learning Techniques in Clinical Vision Sciences.Noninvasive fetal trisomy detection by multiplexed semiconductor sequencing: a barcoding analysis strategy.Recognizing patterns of visual field loss using unsupervised machine learning.Machine learning techniques for the optimization of joint replacements: Application to a short-stem hip implant.Naïve Bayes classification in RFacilitated assessment of tissue loss following traumatic brain injuryArtificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.Prediction of periventricular leukomalacia. Part II: Selection of hemodynamic features using computational intelligenceFederated Tensor Factorization for Computational Phenotyping.A robust multi-class feature selection strategy based on Rotation Forest Ensemble algorithm for diagnosis of Erythemato-Squamous diseases.Application of support vector machine in cancer diagnosis.A Robot-based platform to measure multiple enzyme activities in Arabidopsis using a set of cycling assays: comparison of changes of enzyme activities and transcript levels during diurnal cycles and in prolonged darkness.Predicting Quality of Life Changes in Hemodialysis Patients Using Machine Learning: Generation of an Early Warning System.Radiomics in paediatric neuro-oncology: A multicentre study on MRI texture analysis.Expert system classifier for adaptive radiation therapy in prostate cancer.Identification and Clinical Translation of Biomarker Signatures: Statistical Considerations.Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods.The application of machine learning techniques as an adjunct to clinical decision making in alcohol dependence treatment.The Use of Cardiac Orienting Responses as an Early and Scalable Biomarker of Alcohol-Related Neurodevelopmental Impairment.
P2860
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P2860
Machine learning for medical diagnosis: history, state of the art and perspective
description
2001 nî lūn-bûn
@nan
2001 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2001 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2001年の論文
@ja
2001年論文
@yue
2001年論文
@zh-hant
2001年論文
@zh-hk
2001年論文
@zh-mo
2001年論文
@zh-tw
2001年论文
@wuu
name
Machine learning for medical diagnosis: history, state of the art and perspective
@ast
Machine learning for medical diagnosis: history, state of the art and perspective
@en
Machine learning for medical diagnosis: history, state of the art and perspective.
@nl
type
label
Machine learning for medical diagnosis: history, state of the art and perspective
@ast
Machine learning for medical diagnosis: history, state of the art and perspective
@en
Machine learning for medical diagnosis: history, state of the art and perspective.
@nl
altLabel
Machine learning for medical diagnosis: history, state of the art and perspective.
@en
prefLabel
Machine learning for medical diagnosis: history, state of the art and perspective
@ast
Machine learning for medical diagnosis: history, state of the art and perspective
@en
Machine learning for medical diagnosis: history, state of the art and perspective.
@nl
P1476
Machine learning for medical diagnosis: history, state of the art and perspective
@en
Machine learning for medical diagnosis: history, state of the art and perspective.
@en
P2093
Igor Kononenko
Kononenko I
P304
P356
10.1016/S0933-3657(01)00077-X
P577
2001-08-01T00:00:00Z