Predicting Risk of Suicide Attempt Using History of Physical Illnesses From Electronic Medical Records

Por Karmakar, Chandan, Luo, Wei, Tran, Truyen, Berk, Michael, Venkatesh, Svetha
Publicado no JMIR Ment Health (2016)

Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data

Por Gopakumar, Shivapratap, Tran, Truyen, Luo, Wei, Phung, Dinh, Venkatesh, Svetha
Publicado no JMIR Med Inform (2016)

Screening for post 32-week preterm birth risk: how helpful is routine perinatal data collection?

Por Luo, Wei, Huning, Emily Y-S, Tran, Truyen, Phung, Dinh, Venkatesh, Svetha
Publicado no Heliyon (2016)

Stability, Consistency and Performance of Distribution Entropy in Analysing Short Length Heart Rate Variability (HRV) Signal

Por Karmakar, Chandan, Udhayakumar, Radhagayathri K., Li, Peng, Venkatesh, Svetha, Palaniswami, Marimuthu
Publicado no Front Physiol (2017)

Consistency of the Health of the Nation Outcome Scales (HoNOS) at inpatient-to-community transition

Por Luo, Wei, Harvey, Richard, Tran, Truyen, Phung, Dinh, Venkatesh, Svetha, Connor, Jason P
Publicado no BMJ Open (2016)

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

Por Tran, Truyen, Luo, Wei, Phung, Dinh, Harvey, Richard, Berk, Michael, Kennedy, Richard Lee, Venkatesh, Svetha
Publicado em 2014

A framework for feature extraction from hospital medical data with applications in risk prediction

Por Tran, Truyen, Luo, Wei, Phung, Dinh, Gupta, Sunil, Rana, Santu, Kennedy, Richard Lee, Larkins, Ann, Venkatesh, Svetha
Publicado no BMC Bioinformatics (2014)

Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

Por Luo, Wei, Nguyen, Thin, Nichols, Melanie, Tran, Truyen, Rana, Santu, Gupta, Sunil, Phung, Dinh, Venkatesh, Svetha, Allender, Steve
Publicado no PLoS One (2015)

Rapid Bayesian optimisation for synthesis of short polymer fiber materials

Por Li, Cheng, Rubín de Celis Leal, David, Rana, Santu, Gupta, Sunil, Sutti, Alessandra, Greenhill, Stewart, Slezak, Teo, Height, Murray, Venkatesh, Svetha
Publicado no Sci Rep (2017)

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Por Luo, Wei, Phung, Dinh, Tran, Truyen, Gupta, Sunil, Rana, Santu, Karmakar, Chandan, Shilton, Alistair, Yearwood, John, Dimitrova, Nevenka, Ho, Tu Bao, Venkatesh, Svetha, Berk, Michael
Publicado no J Med Internet Res (2016)

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Por Gupta, Sunil, Tran, Truyen, Luo, Wei, Phung, Dinh, Kennedy, Richard Lee, Broad, Adam, Campbell, David, Kipp, David, Singh, Madhu, Khasraw, Mustafa, Matheson, Leigh, Ashley, David M, Venkatesh, Svetha
Publicado em 2014

Identification and outcomes of clinical phenotypes in amyotrophic lateral sclerosis/motor neuron disease: Australian National Motor Neuron Disease observational cohort

Por Talman, Paul, Duong, Thi, Vucic, Steve, Mathers, Susan, Venkatesh, Svetha, Henderson, Robert, Rowe, Dominic, Schultz, David, Edis, Robert, Needham, Merrilee, Macdonnell, Richard, McCombe, Pamela, Birks, Carol, Kiernan, Matthew
Publicado no BMJ Open (2016)

Randomised controlled trial of an iPad based early intervention for autism: TOBY playpad study protocol

Por Granich, Joanna, Dass, Alena, Busacca, Margherita, Moore, Dennis, Anderson, Angelika, Venkatesh, Svetha, Duong, Thi, Vellanki, Pratibha, Richdale, Amanda, Trembath, David, Cairns, Darin, Marshall, Wendy, Rodwell, Tania, Rayner, Madeleine, Whitehouse, Andrew J. O.
Publicado no BMC Pediatr (2016)

Ageing, Chronic Disease and Injury: A Study in Western Victoria (Australia)

Por Sajjad, M. Amber, Holloway, Kara L., Kotowicz, Mark A., Livingston, Patricia M., Khasraw, Mustafa, Hakkennes, Sharon, Dunning, Trisha L., Brumby, Susan, Page, Richard S., Pedler, Daryl, Sutherland, Alasdair, Venkatesh, Svetha, Brennan-Olsen, Sharon L., Williams, Lana J., Pasco, Julie A.
Publicado no J Public Health Res (2016)