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Hopkins, Pma, Kermeen, FD, Tsang, B, Daniels, TWV, Seale, H, Bec, C and Chambers, DC (2009). Preceeding Respiratory Viral Infection Is a Strong Risk Factor for Fungal infection in Lung Transplant Recipients. In: Journal of Heart and Lung Transplantation. 29th Annual Meeting and Scientific Session of the International-Society-for-Heart-and-Lung-Transplantation, Paris France, (S160-S160). Apr 22-25, 2009. 22   0
Miller, Francis J., Rosenfeldt, Franklin L., Zhang, Chunfang, Linnane, Anthony W. and Nagley, Phillip (2003) Precise determination of mitochondrial DNA copy number in human skeletal and cardiac muscle by a PCR-based assay: Lack of change of copy number with age. Nucleic Acids Research, 31 11: e61-1-e61-7. doi:10.1093/nar/gng060 82   113 0 9
Jayaraman, Ramesh, Reddy, Venkatesh P., Pasha, Mohammed Khalid, Wang, Haishan, Sangthongpitag, Kanda, Yeo, Pauline, Hu, Chang Yong, Wu, Xiaofeng, Xin, Liu, Goh, Evelyn, New, Lee Sun and Ethirajulu, Kantharaj (2011) Preclinical metabolism and disposition of SB939 (Pracinostat), an orally active histone deacetylase inhibitor, and prediction of human pharmacokinetics. Drug Metabolism and Disposition, 39 12: 2219-2232. doi:10.1124/dmd.111.041558 63   9 Cited 12 times in Scopus12 0
McMillian, James R. (2011). Preclinical models of wounds and healing. Animal models of wound healing, scar formation and burns. In: 2nd Australasian Wound and Tissue Repair Society Meeting, Perth, Western Australia, (). 22-24 March, 2010. 92  
Hare, James L., Leano, Rodel L., Jenkins, Carly, Brown, Joseph and Marwick, Thomas H. (2008). Pre-clinical myocardial dysfunction is detected by strain/strain rate before conventional measure in patients undergoing adjuvant breast cancer treatment with Trastuzumab (Herceptin). In: A. DeMaria, Journal of the American College of Cardiology. 57th Annual Scientific Session of the American College of Cardiology, Chicago, USA, (A134-A134). 29th March - 1st April, 2008. doi:10.1016/j.jacc.2008.02.006 87   0 0
Hare, James L., Leano, Rodel, Jenkins, Carly and Marwick, Thomas H. (2008). Preclinical Myocardial Dysfunction is Detected by Strain/Strain Rate before Conventional Measures in Patients Undergoing Adjuvant Breast Cancer Treatment with Trastuzumab (Herceptin). In: Jeremy Richmond, Heart, Lung and Circulation: Abstracts of the Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand. Annual Scientific Meeting of the Cardiac Society of Australia and New Zealand, Adelaide, S. A., (S46-S46). 7th - 10th August, 2008. doi:10.1016/j.hlc.2008.05.106 93   0
Bihari, Shailesh, Maiden, Matthew, Deane, Adam, Fuchs, Ralph, Fraser, John, Bersten, Andrew D. and Bellomo, Rinaldo (2015) Preclinical research in critical care - the Australasian perspective. Critical Care and Resuscitation, 17 3: 151-152. 2   2 0
Gu, Zi, Zuo, Hualia, Li, Li, Wu, Aihua and Xu, Zhi Ping (2015) Pre-coating layered double hydroxide nanoparticles with albumin to improve colloidal stability and cellular uptake. Journal of Materials Chemistry B, 3 16: 3331-3339. doi:10.1039/c5tb00248f 35   8 Cited 8 times in Scopus8 0
Dekker Nitert, M., Barrett, H. L., de Jersey, S., Matusiak, K., McIntyre, H. D. and Callaway, L. K. (2014). Preconception care and barriers to addressing overweight and obesity: a focus on weight loss advice and weight loss strategies. In Handbook of diet and nutrition in the menstrual cycle, periconception and fertility (pp. 327-342) Wageningen, Netherlands: Wageningen Academic Publishers. doi:10.3920/978-90-8686-767-7.020 120 16 0
Richardson, Philip, Greenslade, Jaimi, Shanmugathasan, Sulochana, Doucet, Katherine, Widdicombe, Neil, Chu, Kevin and Brown, Anthony (2015) PREDICT: a diagnostic accuracy study of a tool for predicting mortality within one year: who should have an advance healthcare directive?. Palliative Medicine, 29 1: 31-37. doi:10.1177/0269216314540734 19   1 0 21
Adegbija, Odewumi, Hoy, Wendy and Wang, Zhiqiang (2015): Predicting absolute risk of Type 2 Diabetes using age and waist circumference values in an Aboriginal Australian community. The University of Queensland. Dataset.    
Adegbija, Odewumi, Hoy, Wendy and Wang, Zhiqiang (2015) Predicting absolute risk of type 2 diabetes using age and waist circumference values in an Aboriginal Australian community. PLoS One, 10 4: 1-10. doi:10.1371/journal.pone.0123788 39   1 Cited 1 times in Scopus1 0
Abbott, R.A., Atkin, L.M. and Davies, P.S.W. (2005) Predicting adult height in Turner syndrome. European Journal of Endocrinology, 152 6: 917-917. doi:10.1530/eje.1.01925 130   1 Cited 1 times in Scopus1 0
Mitchell, Jason A., Subramanian, Rajesh, White, Christopher J., Soukas, Peter A., Almagor, Yaron, Stewart, Richard E. and Rosenfield, Kenneth (2007) Predicting blood pressure improvement in hypertensive patients after renal artery stent placement: Renal fractional flow reserve. Catheterization and Cardiovascular Interventions, 69 5: 685-689. doi:10.1002/ccd.21095 38   50 Cited 64 times in Scopus64 0
Olsson, Katherine A., Kenardy, Justin A., De Young, Alexandra C. and Spence, Susan H. (2008) Predicting children's post-traumatic stress symptoms following hospitalisation for accidental injury: Combining the Child Trauma Screening Questionnaire and health rate. Journal of Anxiety Disorders, 22 8: 1447-1453. doi:10.1016/j.janxdis.2008.02.007 111   14 Cited 14 times in Scopus14 0
Irvine, K. M., Wockner, L. F., Shanker, M., Fagan, K. J., Horsfall, L. U., Fletcher, L. M., Ungerer, J., Pretorius, C. J., Miller, G. C., Clouston, A. D., Lampe, G. and Powell, E. E. (2015). Predicting clinical outcomes in chronic liver disease: the ELF test is superior to histology and simple scores. In: Gastro 2015 GESA-AGW and WGO International Congress, Gastroenterological Society of Australia Australian Gastroenterology Week 2015 | World Congress of Gastroenterology, Brisbane, Queensland, Australia, (104-105). 28 September-2 October 2015. doi:10.1111/jgh.13093     0 0
Delaney, J. T., Ramirez, A. H., Bowton, E., Pulley, J. M., Basford, M. A., Schildcrout, J. S., Shi, Y., Zink, R., Oetjens, M., Xu, H., Cleator, J. H., Jahangir, E., Ritchie, M. D., Masys, D. R., Roden, D. M., Crawford, D. C. and Denny, J. C. (2012) Predicting clopidogrel response using DNA samples linked to an electronic health record. Clinical Pharmacology and Therapeutics, 91 2: 257-263. doi:10.1038/clpt.2011.221     52 Cited 58 times in Scopus58 2
Schaefer, B. R., ESichter, R., Catts, S. and Frost, A. D. J. (2005). Predicting duration of untreated psychosis (DUP): Patient characteristics associated with delay in treatment. In: Psychiatry in a changing world. The Royal Aust & NZ College of Psychiatrists 40th Congress, Sydney, (A40-A40). 22-26 May, 2005. 71  
Zubin, Grover and Peter, Lewindon (2015) Predicting endoscopic Crohn's disease activity before and after induction therapy in children: A comprehensive assessment of PCDAI, CRP, and fecal calprotectin. Inflammatory Bowel Diseases, 21 6: 1386-1391. doi:10.1097/MIB.0000000000000388 20   2 Cited 2 times in Scopus2 1
Truby, H., Davies, P. S. W., Cojean, K., Batch, J. A. and Elliott, S. A. (2008). Predicting energy requirements in obese adolescents: Getting an accurate picture?. In: International Journal of Body Composition Research. Proceedings of the International Symposium in In Vivo Body Composition Studies. 8th International Symposium on In Vivo Body Composition Studies, New York City, N.Y. USA, (69-69). 9 -12 July 2008. 55  
Coleman, Andrea, Weir, Kelly, Ware, Robert S. and Boyd, Roslyn (2015) Predicting functional communication ability in children with cerebral palsy at school entry. Developmental Medicine and Child Neurology, 57 3: 279-285. doi:10.1111/dmcn.12631 25   1 Cited 3 times in Scopus3 2
Black, Emma B. and Mildred, Helen (2013) Predicting impulsive self-injurious behavior in a sample of adult women. Journal of Nervous and Mental Disease, 201 1: 72-75. doi:10.1097/NMD.0b013e31827ab1da 17   1 Cited 1 times in Scopus1 1
Sabdia, S., Greer, R. M., Prior, T. and Kumar, S. (2015) Predicting intrapartum fetal compromise using the fetal cerebro-umbilical ratio. Placenta, 36 5: 594-598. doi:10.1016/j.placenta.2015.01.200 62 1 3 Cited 3 times in Scopus3 1
Spittle, Alicia J., Boyd, Roslyn N., Inder, Terrie, E. and Doyle, Lex, W. (2009) Predicting motor development in very preterm infants at 12 months' corrected age: The role of qualitative magnetic resonance imaging and general movements assessments. Pediatrics, 123 2: 512-517. doi:10.1542/peds.2008-0590 71   68 Cited 81 times in Scopus81 0
Krishnan, Manju, Beck, Sue, Havelock, Will, Eeles, Eamonn, Hubbard, Ruth E. and Johansen, Antony (2014) Predicting outcome after hip fracture: using a frailty index to integrate comprehensive geriatric assessment results. Age and Ageing, 43 1: 122-126. doi:10.1093/ageing/aft084 26   26 Cited 33 times in Scopus33 11
Krishnan, M., Beck, S., Cowen, O., Hughes, M., Havelock, W., Eeles, E., Hubbard, R. and Johansen, A. (2013). Predicting outcome after hip fracture: using frailty index to integrate comprehensive geriatric assessment results. In: British Geriatrics Society Communications to the Spring Meeting. British Geriatrics Society, Belfast, Ireland, (iii16-iii17). 17-19 April 2013. doi:10.1093/ageing/aft101 30   1 0
Bradman, Kate, Borland, Meredith and Pascoe, Elaine (2012) Predicting patient disposition in a paediatric emergency department. Journal of Paediatrics and Child Health, 50 10: E39-E44. doi:10.1111/jpc.12011 24   4 Cited 4 times in Scopus4 1
Brooks, Gabriel C., Lee, Byron K., Rao, Rajni, Lin, Feng, Morin, Daniel P., Zweibel, Steven L., Buxton, Alfred E., Pletcher, Mark J., Vittinghoff, Eric and Olgin, Jeffrey E. (2016) Predicting persistent left ventricular dysfunction following myocardial infarction: the PREDICTS study. Journal of the American College of Cardiology, 67 10: 1186-1196. doi:10.1016/j.jacc.2015.12.042     2 Cited 3 times in Scopus3 2
Mitra, J., Carey, L., Fripp, J., Shen, K., Pannek, K., Bourgeat, P., Salvado, O., Campbell, B., Connelly, A., Palmer, S. and Rose, S. (2014). Predicting poststroke depression from structural brain connectivity. In: 25th Annual Scientific Meeting of the Stroke Society of Australasia, Hamilton Island, Australia, (44-44). 30 July-1 August 2014. doi:10.1111/ijs.12298 23   0 0
DE Sutter, An, Lemiengre, Marieke, Van Maele, Gorges, van Driel, Mieke, De Meyere, Marc, Christiaens, Thierry and De Maeseneer, Jan (2006). Predicting prognosis and effect of antibiotic treatment in rhinosinusitis. In: WONCA. WONCA Europe Regional Conference, Amsterdam Netherlands, (486-493). 01-04 June 2004. doi:10.1370/afm.600 33   15 Cited 15 times in Scopus15 6
Mehra, M. R., Lavie, C. J. and Milani, R. V. (1996) Predicting prognosis in advanced heart failure: Use of exercise indices. Chest, 110 2: 310-312. doi:10.1378/chest.110.2.310 35   8 0 0
Porceddu, S. V., Sidhom, M., Foote, M., Burmeister, E., Stoneley, A., Hawwari, B. El, Milross, C., Kenny, L., Poulsen, M. and Coman, W. B. (2008) Predicting regional control based on pretreatment nodal size in squamous cell carcinoma of the head and neck treated with chemoradiotherapy: A clinican's guide. Journal of Medical Imaging and Radiation Oncology, 52 5: 491-496. doi:10.1111/j.1440-1673.2008.02001.x 88   2 Cited 2 times in Scopus2 3
Elliott, Sarah A., Davidson, Zoe E., Davies, Peter S.W. and Truby, Helen (2012) Predicting resting energy expenditure in boys with Duchenne muscular dystrophy. European Journal of Paediatric Neurology, 16 6: 631-635. doi:10.1016/j.ejpn.2012.02.011 41   6 Cited 6 times in Scopus6 0
Branagan, H., Meijer, R., Schaafstra, A., Case, Colin, Boersma, E., Poldermans, D. and Marwick, T. H. (2007). Predicting risk of cardiac events after major noncardiac surgery: development of a risk score combining clinical risk markers and dobutamine echo. In: Abstracts for the Cardiac Society of Australia and New Zealand Annual Scientific Meeting and the International Society for Heart Research, Australasian Section, Annual Scientific Meeting. Cardiac Society of Aust and NZ Annual Scientific Meeting, Christchurch, NZ, (S93-S93). 9-12 August 2007. 39  
Urwin, H. R., Jones, P. W., Harden, P. N., Ramsay, H. M., Hawley, C. M., Nicol, D. L. and Fryer, A. A. (2009) Predicting Risk of Nonmelanoma Skin Cancer and Premalignant Skin Lesions in Renal Transplant Recipients. Transplantation, 87 11: 1667-1671. doi:10.1097/TP.0b013e3181a5ce2e 78   18 Cited 24 times in Scopus24 0
Magnusson, BM, Pugh, JW and Roberts, MS (2005) Predicting skin flux for minimal toxicological exposure or maximal therapeutic delivery. Journal of Investigative Dermatology, 125 3: A11-A11. 45   0
Wiechers, J. W., Watkinson, A. C., Cross, S. E. and Roberts, M. S. (2012) Predicting skin penetration of actives from complex cosmetic formulations: an evaluation of inter formulation and inter active effects during formulation optimization for transdermal delivery. International Journal of Cosmetic Science, 34 6: 525-535. doi:10.1111/ics.12001 69   8 Cited 9 times in Scopus9 1
Baxter, Kimberley A., Ware, Robert S., Batch, Jennifer A. and Truby, Helen (2013) Predicting success: factors associated with weight change in obese youth undertaking a weight management program. Obesity Research and Clinical Practice, 7 2: E147-E154. doi:10.1016/j.orcp.2011.09.004 149 1 5 Cited 6 times in Scopus6 0
Pearce, C.M. and Martin, G. (1994) Predicting suicide attempts among adolescents. Acta Psychiatrica Scandinavica, 90 5: 324-328. doi:10.1111/j.1600-0447.1994.tb01601.x 50   31 0
Bilous, M., Ades, C., Armes, J., Bishop, J., Brown, R., Cooke, B., Cummings, M., Farshid, G., Field, A., Morey, A., McKenzie, P., Raymond, W., Robbins, P. and Tan, L. (2003) Predicting the HER2 status of breast cancer from basic histopathology data: an analysis of 1500 breast cancers as part of the HER2000 International Study. Breast, 12 2: 92-98. doi:10.1016/S0960-9776(02)00273-4 103   54 Cited 63 times in Scopus63 0
Yates, Jason, Conwell, Louise, Johnson, Stephanie, McMahon, Sarah, Hughes, Ian, Harris, Mark, Batch, Jennifer and Cotterill, Andrew (2012). Predicting the length of honeymoon in newly diagnosed children with type 1 diabetes mellitus based on age, initial HbA1c and acid base status. In: Australasian Paediatric Endocrine Group Annual Scientific Meeting. Australasian Paediatric Endocrine Group Annual Scientific Meeting, Queenstown, New Zealand, (). 29 July - 2 August 2012. 42  
Brown, Elizabeth, Owen, Rebecca, Harden, Fiona, Mengersen, Kerrie, Oestreich, Kimberley, Houghton, Whitney, Poulsen, Michael, Harris, Selina, Lin, Charles and Porceddu, Sandro (2015) Predicting the need for adaptive radiotherapy in head and neck cancer. Radiotherapy and Oncology, 116 1: 57-63. doi:10.1016/j.radonc.2015.06.025 12   7 Cited 5 times in Scopus5 1
Morosini, A. and Davies, M. W. (2004) Predicting the Need for Ventilation in Term and Near-Term Neonates. Journal of Paediatrics and Child Health, 40 8: 438-443. doi:10.1111/j.1440-1754.2004.00425.x 413 414 4 Cited 5 times in Scopus5 0
Gastal, Fábio L., Andreoli, Sérgio B., Quintana, Maria Inês S., Gameiro, Maurício Almeida, Leite, Sérgio O. and McGrath, John (2000) Predicting the revolving door phenomenon among patients with schizophrenic, affective disorders and non-organic psychoses. Revista de Saude Publica, 34 3: 280-285. doi:10.1590/S0034-89102000000300011 154 1 19 0 0
Kyle, Samuel D., Law, W. Phillip and Miles, K. A. (2013) Predicting tumour response. Cancer Imaging, 13 3: 381-390. doi:10.1102/1470-7330.2013.9039 46 2 Cited 2 times in Scopus2 0
Lee, Sang Hong, van der Werf, Julius H. J., Hayes, Ben J., Goddard, Michael E. and Visscher, Peter M. (2008) Predicting unobserved phenotypes for complex traits from whole-genome SNP data. PLoS Genetics, 4 10: . doi:10.1371/journal.pgen.1000231 30   102 Cited 108 times in Scopus108 9
de Silva, D. J., Kwan, A., Bunce, C. and Bainbridge, J. (2008) Predicting visual outcome following retinectomy for retinal detachment. British Journal of Ophthalmology, 92 7: 954-958. doi:10.1136/bjo.2007.131540 23   22 Cited 29 times in Scopus29 0
Crouch, A., Cheung, V., Gray, L., Yelland, C. and Salih, S. (2009). Predicting walking time on a geriatric rehabilitation ward. In: Australasian Journal on Ageing. The Australian & New Zealand Society for Geriatric Medicine Annual Scientific Meeting, “Of Bones, Jointes and Sinewes”: Musculoskeletal Medicine at the end of The Bone and Joint Decade. The Australian & New Zealand Society for Geriatric Medicine Annual Scientific Meeting, “Of Bones, Jointes and Sinewes”: Musculoskeletal Medicine at the end of The Bone and Joint Decade, Fremantle, Australia, (A7-A7). 7–9 September, 2009. doi:10.1111/j.1741-6612.2009.00386.x 76   0 0
Verstraete, Evelien Hilde, Blot, Koen, Mahieu, Ludo, Vogelaers, Dirk and Blot, Stijn (2015) Prediction models for neonatal health care-associated sepsis: A meta-analysis. Pediatrics, 135 4: e1002-e1014. doi:10.1542/peds.2014-3226 25   6 Cited 4 times in Scopus4 5
Patel, Dharmendrakumar A., Lavie, Carl J., Gilliland, Yvonne E., Shah, Sangeeta B., Dinshaw, Homeyar K. and Milani, Richard V. (2015) Prediction of All-Cause Mortality by the Left Atrial Volume Index in Patients With Normal Left Ventricular Filling Pressure and Preserved Ejection Fraction. Mayo Clinic Proceedings, 90 11: 1499-1505. doi:10.1016/j.mayocp.2015.07.021     2 Cited 2 times in Scopus2 26

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