scholarly journals Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data

2016 ◽  
Vol 38 (2) ◽  
pp. 704-714 ◽  
Author(s):  
Sanne de Wit ◽  
Tim B. Ziermans ◽  
M. Nieuwenhuis ◽  
Patricia F. Schothorst ◽  
Herman van Engeland ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Machine Learning Techniques ◽  
Imaging Data ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Learning Techniques ◽  
Ultra High Risk ◽  
Brain Imaging Data

Machine Learning for Neurodegenerative Disorder Diagnosis — Survey of Practices and Launch of Benchmark Dataset

2018 ◽  
Vol 27 (03) ◽  
pp. 1850011 ◽  
Author(s):  
Athanasios Tagaris ◽  
Dimitrios Kollias ◽  
Andreas Stafylopatis ◽  
Georgios Tagaris ◽  
Stefanos Kollias
Keyword(s):  
Machine Learning ◽  
Neurodegenerative Disorder ◽  
Developed Countries ◽  
Machine Learning Techniques ◽  
Network Architectures ◽  
Imaging Data ◽  
Learning Techniques ◽  
Medical Examinations

Neurodegenerative disorders, such as Alzheimer’s and Parkinson’s, constitute a major factor in long-term disability and are becoming more and more a serious concern in developed countries. As there are, at present, no effective therapies, early diagnosis along with avoidance of misdiagnosis seem to be critical in ensuring a good quality of life for patients. In this sense, the adoption of computer-aided-diagnosis tools can offer significant assistance to clinicians. In the present paper, we provide in the first place a comprehensive recording of medical examinations relevant to those disorders. Then, a review is conducted concerning the use of Machine Learning techniques in supporting diagnosis of neurodegenerative diseases, with reference to at times used medical datasets. Special attention has been given to the field of Deep Learning. In addition to that, we communicate the launch of a newly created dataset for Parkinson’s disease, containing epidemiological, clinical and imaging data, which will be publicly available to researchers for benchmarking purposes. To assess the potential of the new dataset, an experimental study in Parkinson’s diagnosis is carried out, based on state-of-the-art Deep Neural Network architectures and yielding very promising accuracy results.

scholarly journals Neurocognitive and Clinical Predictors of Long-Term Outcome in Adolescents at Ultra-High Risk for Psychosis: A 6-Year Follow-Up

PLoS ONE ◽  
2014 ◽  
Vol 9 (4) ◽  
pp. e93994 ◽  
Author(s):  
Tim Ziermans ◽  
Sanne de Wit ◽  
Patricia Schothorst ◽  
Mirjam Sprong ◽  
Herman van Engeland ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Predictors ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Ultra High Risk

Adolescents at ultra-high risk for psychosis: Long-term outcome of individuals who recover from their at-risk state

2014 ◽  
Vol 24 (6) ◽  
pp. 865-873 ◽  
Author(s):  
S. de Wit ◽  
P.F. Schothorst ◽  
B. Oranje ◽  
T.B. Ziermans ◽  
S. Durston ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Ultra High Risk

717 – Clinical measures trump neurocognition in predicting long-term outcome for adolescents at ultra-high risk for psychosis

2013 ◽  
Vol 28 ◽  
pp. 1
Author(s):  
T. Ziermans ◽  
S. de Wit ◽  
P. Schothorst ◽  
M. Sprong ◽  
H. van Engeland ◽  
...  
Keyword(s):  
High Risk ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Ultra High Risk ◽  
Clinical Measures

Long-term outcome for very high-risk prostate cancer treated primarily with a triple modality approach to include permanent interstitial brachytherapy

Brachytherapy ◽  
2012 ◽  
Vol 11 (4) ◽  
pp. 250-255 ◽  
Author(s):  
Nathan Bittner ◽  
Gregory S. Merrick ◽  
Wayne M. Butler ◽  
Robert W. Galbreath ◽  
Jonathan Lief ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Interstitial Brachytherapy ◽  
Term Outcome ◽  
Long Term Outcome ◽  
High Risk Prostate Cancer ◽  
Risk Prostate Cancer ◽  
Modality Approach ◽  
Very High
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