Ngā hua rapu - Dhiman, Paula

Availability and Quality of Coronary Heart Disease Family History in Primary Care Medical Records: Implications for Cardiovascular Risk Assessment mā Dhiman, Paula, Kai, Joe, Horsfall, Laura, Walters, Kate, Qureshi, Nadeem

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Does bone mineral density improve the predictive accuracy of fracture risk assessment? A prospective cohort study in Northern Denmark mā Dhiman, Paula, Andersen, Stig, Vestergaard, Peter, Masud, Tahir, Qureshi, Nadeem

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Antidepressant use and risk of adverse outcomes in older people: population based cohort study mā Coupland, Carol, Dhiman, Paula, Morriss, Richard, Arthur, Antony, Barton, Garry, Hippisley-Cox, Julia

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A review found inadequate reporting of case–control studies of risk factors for pancreatic cancer mā MacCarthy, Angela, Dhiman, Paula, Kirtley, Shona, Logullo, Patricia, Copsey, Bethan, Collins, Gary S.

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GoodReports: developing a website to help health researchers find and use reporting guidelines mā Struthers, Caroline, Harwood, James, de Beyer, Jennifer Anne, Dhiman, Paula, Logullo, Patricia, Schlüssel, Michael

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Psychological morbidity and return to work after injury: multicentre cohort study mā Kendrick, Denise, Dhiman, Paula, Kellezi, Blerina, Coupland, Carol, Whitehead, Jessica, Beckett, Kate, Christie, Nicola, Sleney, Judith, Barnes, Jo, Joseph, Stephen, Morriss, Richard

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Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved mā Dhiman, Paula, Ma, Jie, Navarro, Constanza Andaur, Speich, Benjamin, Bullock, Garrett, Damen, Johanna AA, Kirtley, Shona, Hooft, Lotty, Riley, Richard D, Van Calster, Ben, Moons, Karel G.M., Collins, Gary S.

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Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques mā Andaur Navarro, Constanza L, Damen, Johanna A A G, Takada, Toshihiko, Nijman, Steven W J, Dhiman, Paula, Ma, Jie, Collins, Gary S, Bajpai, Ram, Riley, Richard D, Moons, Karel GM, Hooft, Lotty

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Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review mā Andaur Navarro, Constanza L, Damen, Johanna A A, Takada, Toshihiko, Nijman, Steven W J, Dhiman, Paula, Ma, Jie, Collins, Gary S, Bajpai, Ram, Riley, Richard D, Moons, Karel G M, Hooft, Lotty

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Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review mā Andaur Navarro, Constanza L., Damen, Johanna A. A., Takada, Toshihiko, Nijman, Steven W. J., Dhiman, Paula, Ma, Jie, Collins, Gary S., Bajpai, Ram, Riley, Richard D., Moons, Karel G. M., Hooft, Lotty

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Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review mā Dhiman, Paula, Ma, Jie, Andaur Navarro, Constanza L., Speich, Benjamin, Bullock, Garrett, Damen, Johanna A. A., Hooft, Lotty, Kirtley, Shona, Riley, Richard D., Van Calster, Ben, Moons, Karel G. M., Collins, Gary S.

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Risk of bias of prognostic models developed using machine learning: a systematic review in oncology mā Dhiman, Paula, Ma, Jie, Andaur Navarro, Constanza L., Speich, Benjamin, Bullock, Garrett, Damen, Johanna A. A., Hooft, Lotty, Kirtley, Shona, Riley, Richard D., Van Calster, Ben, Moons, Karel G. M., Collins, Gary S.

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Multiple cereblon genetic changes are associated with acquired resistance to lenalidomide or pomalidomide in multiple myeloma mā Gooding, Sarah, Ansari-Pour, Naser, Towfic, Fadi, Ortiz Estévez, María, Chamberlain, Philip P., Tsai, Kao-Tai, Flynt, Erin, Hirst, Marissa, Rozelle, Dan, Dhiman, Paula, Neri, Paola, Ramasamy, Karthik, Bahlis, Nizar, Vyas, Paresh, Thakurta, Anjan

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Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intellig... mā Collins, Gary S, Dhiman, Paula, Andaur Navarro, Constanza L, Ma, Jie, Hooft, Lotty, Reitsma, Johannes B, Logullo, Patricia, Beam, Andrew L, Peng, Lily, Van Calster, Ben, van Smeden, Maarten, Riley, Richard D, Moons, Karel GM

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Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal mā Wynants, Laure, Van Calster, Ben, Collins, Gary S, Riley, Richard D, Heinze, Georg, Schuit, Ewoud, Bonten, Marc M J, Damen, Johanna A A, Debray, Thomas P A, De Vos, Maarten, Dhiman, Paula, Haller, Maria C, Harhay, Michael O, Henckaerts, Liesbet, Kreuzberger, Nina, Lohmann, Anna, Luijken, Kim, Ma, Jie, Andaur Navarro, Constanza L, Reitsma, Johannes B, Sergeant, Jamie C, Shi, Chunhu, Skoetz, Nicole, Smits, Luc J M, Snell, Kym I E, Sperrin, Matthew, Spijker, René, Steyerberg, Ewout W, Takada, Toshihiko, van Kuijk, Sander M J, van Royen, Florien S, Wallisch, Christine, Hooft, Lotty, Moons, Karel G M, van Smeden, Maarten

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