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JAMA : the journal of the American Medical Association, ISSN 0098-7484, 10/2011, Volume 306, Issue 15, pp. 1688 - 1698
... for the purposes of hospital comparison. OBJECTIVE To summarize validated readmission risk prediction models, describe their performance, and assess suitability for clinical or administrative use... 
MEDICINE, GENERAL & INTERNAL | QUALITY-OF-CARE | GENERAL MEDICINE PATIENTS | PERFORMANCE | HEART-FAILURE | VALIDATION | STATISTICAL-MODELS | PATIENT PREDICTORS | FOLLOW-UP | TRANSITIONS | 30-DAY READMISSION | Outcome Assessment (Health Care) | Patient Readmission | Risk Assessment | Risk Adjustment | Humans | Hospitalization | Models, Statistical | Forecasting | Patient admissions | Risk assessment | Quality of care | Clinical outcomes | Predictions
Journal Article
Journal of the American College of Cardiology, ISSN 0735-1097, 10/2018, Volume 72, Issue 16, pp. 1883 - 1893
Background: Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help... 
coronary artery disease | primary prevention | genomic risk prediction | HEART-DISEASE | CARDIAC & CARDIOVASCULAR SYSTEMS | SCORE | GENETIC RISK | Genomics - statistics & numerical data | Predictive Value of Tests | Risk Assessment - methods | Genome-Wide Association Study | Humans | Middle Aged | Risk Factors | Male | Mass Screening - methods | Multifactorial Inheritance | Coronary Artery Disease - diagnosis | Coronary Artery Disease - genetics | Primary Prevention - methods | Female | Coronary Artery Disease - epidemiology | Genomics - methods | Research Design | United Kingdom - epidemiology | Prevention | Coronary heart disease | Heart attacks | Angioplasty | Lipids | Cardiovascular disease | Genomes | Family medical history | Risk factors | Confidence intervals | Body mass index | Health and safety screening | Population | Genetics | Blood pressure | Heart diseases | Age | Hypertension | Diabetes mellitus | Coronary artery | Health risks | Assessment centers | Trajectories | Risk analysis | Coronary artery disease | Cholesterol | Studies | Disease prevention | Genetic variance | Hospitals | Body mass | Body size | Coronary vessels | Adults | Heritability | Diabetes | Health risk assessment | Smoking | BMI, body mass index | CI, confidence interval | HR, hazard ratio | GRS, genomic risk score(s) | CAD, coronary artery disease
Journal Article
Journal Article
The New England Journal of Medicine, ISSN 0028-4793, 04/2009, Volume 360, Issue 17, pp. 1701 - 1703
Journal Article
2015, ISBN 9780143125082, xvii, 536 pages
.... Drawing on his own groundbreaking work, he examines the world of prediction. 
Bayesian statistical decision theory | Knowledge, Theory of | Methodology | History | Forecasting
Book
by Kaptoge, Stephen and Angelantonio, Emanuele and Pennells, Lisa and Wood, Angela and White, Ian and Gao, Pei and Walker, Mark and Thompson, Alexander and Sarwar, Sheryar and Caslake, Muriel and Butterworth, Adam and Amouyel, Philippe and Assmann, Gerd and Bakker, Stephan and Barr, E.L.M and Barrett-Connor, Elizabeth and Benjamin, Emelia and Björkelund, Cecilia and Brenner, Hermann and Brunner, Eric and Clarke, Robert and Cooper, Jackie and Cremer, P and Cushman, Mary Ann and Dagenais, Gilles R and D'Agostino, Ralph and Dankner, Rachel and Davey-Smith, George and Deeg, Dorly and Dekker, Jacqueline and Engström, G and Folsom, Aaron and Fowkes, F. Gerald R and Gallacher, John and Gaziano, J. Michael and Giampaoli, Simona and Gillum, Richard and Hofman, Albert and Howard, Barbara and Ingelsson, Erik and Iso, Hiroyasu and Jorgensen, Torben and Kiechl, Stefan and Kitamura, A and Kiyohara, Yutaka and Koenig, Wolfgang and Kromhout, Daan and Kuller, Lewis and Lawlor, Debbie and Meade, Tom and Nissinen, Aulikki and Nordestgaard, Børge and Onat, Altan and Panagiotakos, Demosthenes and Psaty, Bruce and Roiguez, Beatriz and Rosengren, Annika and Salomaa, Veikko and Kauhanen, Jussi and Salonen, J.T and Shaffer, Jonathan and Shea, Steven and Ford, Ian and Stehouwer, Coen and Strandberg, Timo and Tipping, Alex and Tosetto, Alberto and Wassertheil-Smoller, Sylvia and Wennberg, Patrik and Westendorp, Rudi and Whincup, Peter and Wilhelmsen, Lars and Woodward, Mark and Lowe, Gordon and Wareham, Nick and Khaw, Kay-Tee and Sattar, Naveed and Packard, Chris and Gudnason, Vilmundur and Ridker, Paul and Pepys, Mark and Thompson, Simon and Danesh, John and The Emerging Risk Factors Collaboration and Emerging Risk Factors and Emerging Risk Factors Collaboration and Sahlgrenska akademin and Institute of Medicine and Göteborgs universitet and Gothenburg University and Sahlgrenska Academy and Institutionen för medicin
The New England journal of medicine, ISSN 1533-4406, 2012, Volume 367, Issue 14, pp. 1310 - 1320
Journal Article
Journal of the American College of Cardiology, ISSN 0735-1097, 02/2014, Volume 63, Issue 7, pp. 636 - 646
Journal Article
The New England journal of medicine, ISSN 1533-4406, 2017, Volume 376, Issue 26, pp. 2507 - 2509
... decisions. But in the “hype cycle” of emerging technologies, machine learning now rides atop the “peak of inflated expectations.” 2 Prediction is not new to medicine... 
MEDICINE, GENERAL & INTERNAL | BIG DATA | Probability | Risk Assessment - methods | Algorithms | Prognosis | Machine Learning | Technology application | Usage | Automobile driving | Artificial intelligence | Machine learning | Motor vehicle driving | Health care | Learning algorithms | Aversion learning | Neural networks | Serial learning | Predictions | Big Data | Health risk assessment | Patients
Journal Article