title: A Comparison of Multi-instance Learning Algorithms

authors: Dong, Lin

subjects: machine learning

abstract: Motivated by various challenging real-world applications, such as drug activity prediction and image retrieval, multi-instance (MI) learning has attracted considerable interest in recent years.  Compared with standard supervised learning, the MI learning task is more difficult as the label information of each training example is incomplete. Many MI algorithms have been proposed. Some of them are specifically designed for MI problems whereas others have been upgraded or adapted from standard single-instance learning algorithms.  Most algorithms have been evaluated on only one or two benchmark datasets, and there is a lack of systematic comparisons of MI learning algorithms.

This thesis presents a comprehensive study of MI learning algorithms that aims to compare their performance and find a suitable way to properly address different MI problems. First, it briefly reviews the history of research on MI learning. Then it discusses five general classes of MI approaches that cover a total of 16 MI algorithms. After that, it presents empirical results for these algorithms that were obtained from 15 datasets which involve five different real-world application domains.  Finally, some conclusions are drawn from these results: (1) applying suitable standard single-instance learners to MI problems can often generate the best result on the datasets that were tested, (2) algorithms exploiting the standard asymmetric MI assumption do not show significant advantages over approaches using the so-called collective assumption, and (3) different MI approaches are suitable for different application domains, and no MI algorithm works best on all MI problems.

text: A Comparison of Multi-instance Learning Algorithms Motivated by various challenging real-world applications, such as drug activity prediction and image retrieval, multi-instance (MI) learning has attracted considerable interest in recent years.  Compared with standard supervised learning, the MI learning task is more difficult as the label information of each training example is incomplete. Many MI algorithms have been proposed. Some of them are specifically designed for MI problems whereas others have been upgraded or adapted from standard single-instance learning algorithms.  Most algorithms have been evaluated on only one or two benchmark datasets, and there is a lack of systematic comparisons of MI learning algorithms.

This thesis presents a comprehensive study of MI learning algorithms that aims to compare their performance and find a suitable way to properly address different MI problems. First, it briefly reviews the history of research on MI learning. Then it discusses five general classes of MI approaches that cover a total of 16 MI algorithms. After that, it presents empirical results for these algorithms that were obtained from 15 datasets which involve five different real-world application domains.  Finally, some conclusions are drawn from these results: (1) applying suitable standard single-instance learners to MI problems can often generate the best result on the datasets that were tested, (2) algorithms exploiting the standard asymmetric MI assumption do not show significant advantages over approaches using the so-called collective assumption, and (3) different MI approaches are suitable for different application domains, and no MI algorithm works best on all MI problems.

year: 2006

title: Repetitive Transcranial Magnetic Stimulation: A Call for Better Data

authors: Wilson, Marcus T.

subjects: Science & Technology

abstract: Repetitive Transcranial Magnetic Stimulation (rTMS) is increasingly used to treat stroke, Parkinson's disease and depression (Fregni et al., 2005; Loo and Mitchell, 2005; Hallet, 2007; O'Reardon et al., 2007; Ridding and Rothwell, 2007). rTMS uses bursts of magnetic pulses to change the excitability and connection strengths of cortical neurons. However, the evidence to inform clinical application is highly inconsistent (Thut and Pascual-Leone, 2010; Hamada et al., 2013) and substantially based on trial and error. Systematic theory is lacking. Typically, in rTMS research, measurements of motor-evoked potential (MEP) are made, often in terms of the strength of the MEP and the length of the cortical silent period that follows. However, the MEP is probably a poor and certainly an indirect measure of changes in the brain (Nicolo et al., 2015), clouding our understanding of rTMS mechanisms. In practice, therefore, particular amplitudes and timing of pulses in an rTMS sequence are selected because they show promise in small subsets of people. However, even basics such as the sign of any change in the outcome measure (e.g., does the MEP increase or decrease?) is debated. Many results show a wide spread in responses. It has become common to talk about “responders” and “non-responders” although evidence for a binary distinction in these two groups is lacking—in reality there is usually a continuum of response often including potentiation in some and depression in others (Nettekoven et al., 2015). Moreover, Héroux et al. (2015) provide evidence that the irreproducibility of results may be due to small sample sizes, unscientific screening of subjects and data, and selective reporting of results.

text: Repetitive Transcranial Magnetic Stimulation: A Call for Better Data Repetitive Transcranial Magnetic Stimulation (rTMS) is increasingly used to treat stroke, Parkinson's disease and depression (Fregni et al., 2005; Loo and Mitchell, 2005; Hallet, 2007; O'Reardon et al., 2007; Ridding and Rothwell, 2007). rTMS uses bursts of magnetic pulses to change the excitability and connection strengths of cortical neurons. However, the evidence to inform clinical application is highly inconsistent (Thut and Pascual-Leone, 2010; Hamada et al., 2013) and substantially based on trial and error. Systematic theory is lacking. Typically, in rTMS research, measurements of motor-evoked potential (MEP) are made, often in terms of the strength of the MEP and the length of the cortical silent period that follows. However, the MEP is probably a poor and certainly an indirect measure of changes in the brain (Nicolo et al., 2015), clouding our understanding of rTMS mechanisms. In practice, therefore, particular amplitudes and timing of pulses in an rTMS sequence are selected because they show promise in small subsets of people. However, even basics such as the sign of any change in the outcome measure (e.g., does the MEP increase or decrease?) is debated. Many results show a wide spread in responses. It has become common to talk about “responders” and “non-responders” although evidence for a binary distinction in these two groups is lacking—in reality there is usually a continuum of response often including potentiation in some and depression in others (Nettekoven et al., 2015). Moreover, Héroux et al. (2015) provide evidence that the irreproducibility of results may be due to small sample sizes, unscientific screening of subjects and data, and selective reporting of results.

year: 2016

title: Exploring Māori and non-Māori mental health nurses' perceptions of Te Whare Tapa Whā: A mixed methods study looking at Māori and non-Māori mental health nurses' perceptions of Te Whare Tapa Whā within the Waikato region

authors: Teinakore, Samantha

subjects: Te Whare Tapa Whā

abstract: Background: Te Whare Tapa Whā is a well-recognised Māori model of health and wellbeing which is embraced within the health system in Aotearoa/ New Zealand. Although it can be applied in different specialties, the impacts generated from this model were first noticed in mental health, as this model was created by Mason Durie who is a psychiatrist. Research has shown this model provided an opportunity for Māori to have a voice in their health.
Objective: This study aims were to explore mental health nurses’ perceptions of the Māori Health model, Te Whare Tapa Whā, and how their beliefs and values may impact them implementing this model into their care.
Methods: A mixed methods approach was utilised for this study. Phase one was about gathering quantitative data, collecting statistical data through surveys. The first phase helped with the formulate interview schedule, which was the beginning of the next phase. Phase two was semi structured interviews which helped with the gathering of qualitative data. Data were analysed using descriptive statistics and thematic analysis.
Participants: Mental health nurses within the Waikato region were the participants for this research study. A survey was distributed to mental health nurses in the Waikato area and 53 responded. After the survey, semi structured one on one interviews were conducted with the researcher. Total of 8 interviews; (n = 6) Māori mental health nurses and (n = 2) Non-Māori mental health nurses.
Results: The survey showed that more than half the nurses had a positive perspective on Te Whare Tapa Whā and felt it was good for nursing care. They were able to identify barriers to implementation. There were mixed responses on feeling supported to use Te Whare Tapa Whā in the workplace. Four over-arching themes were identified from the interviews . These were; Māori, clinical practice, organisation level and individual factors.
Conclusion: Overall, all mental health nurses had a positive perception of Te Whare Tapa Whā and the impacts it can have on nursing care. Most identified barriers which can impact whether they can actually use it in practice. Māori and non-Māori nurses had different depths of knowledge, cultural worldviews and clinical practice experiences, creating complexities with implementation. These beliefs, perceptions and experiences were highlighted in this study.

text: Exploring Māori and non-Māori mental health nurses' perceptions of Te Whare Tapa Whā: A mixed methods study looking at Māori and non-Māori mental health nurses' perceptions of Te Whare Tapa Whā within the Waikato region Background: Te Whare Tapa Whā is a well-recognised Māori model of health and wellbeing which is embraced within the health system in Aotearoa/ New Zealand. Although it can be applied in different specialties, the impacts generated from this model were first noticed in mental health, as this model was created by Mason Durie who is a psychiatrist. Research has shown this model provided an opportunity for Māori to have a voice in their health.
Objective: This study aims were to explore mental health nurses’ perceptions of the Māori Health model, Te Whare Tapa Whā, and how their beliefs and values may impact them implementing this model into their care.
Methods: A mixed methods approach was utilised for this study. Phase one was about gathering quantitative data, collecting statistical data through surveys. The first phase helped with the formulate interview schedule, which was the beginning of the next phase. Phase two was semi structured interviews which helped with the gathering of qualitative data. Data were analysed using descriptive statistics and thematic analysis.
Participants: Mental health nurses within the Waikato region were the participants for this research study. A survey was distributed to mental health nurses in the Waikato area and 53 responded. After the survey, semi structured one on one interviews were conducted with the researcher. Total of 8 interviews; (n = 6) Māori mental health nurses and (n = 2) Non-Māori mental health nurses.
Results: The survey showed that more than half the nurses had a positive perspective on Te Whare Tapa Whā and felt it was good for nursing care. They were able to identify barriers to implementation. There were mixed responses on feeling supported to use Te Whare Tapa Whā in the workplace. Four over-arching themes were identified from the interviews . These were; Māori, clinical practice, organisation level and individual factors.
Conclusion: Overall, all mental health nurses had a positive perception of Te Whare Tapa Whā and the impacts it can have on nursing care. Most identified barriers which can impact whether they can actually use it in practice. Māori and non-Māori nurses had different depths of knowledge, cultural worldviews and clinical practice experiences, creating complexities with implementation. These beliefs, perceptions and experiences were highlighted in this study.

year: 2023