Active learning: A step towards automating medical concept extraction

Objective This paper presents an automatic active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort, and (2) the robustness of incremental active learning framework across different selection criteria and datasets is determined. Materials and methods The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional Random Fields as the supervised method, and least confidence and information density as two selection criteria for active learning framework were used. The effect of incremental learning vs. standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. Two clinical datasets were used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Results The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared to the Random sampling baseline, the saving is at least doubled. Discussion Incremental active learning guarantees robustness across all selection criteria and datasets. The reduction of annotation effort is always above random sampling and longest sequence baselines. Conclusion Incremental active learning is a promising approach for building effective and robust medical concept extraction models, while significantly reducing the burden of manual annotation.

Pedagogical tools designed to promote engagement and active learning in the biomedical sciences and allied health disciplines

Perceiving students, science students especially, as mere consumers of facts and information belies the importance of a need to engage them with the principles underlying those facts and is counter-intuitive to the facilitation of knowledge and understanding. Traditional didactic lecture approaches need a re-think if student classroom engagement and active learning are to be valued over fact memorisation and fact recall. In our undergraduate biomedical science programs across Years 1, 2 and 3 in the Faculty of Health at QUT, we have developed an authentic learning model with an embedded suite of pedagogical strategies that foster classroom engagement and allow for active learning in the sub-discipline area of medical bacteriology. The suite of pedagogical tools we have developed have been designed to enable their translation, with appropriate fine-tuning, to most biomedical and allied health discipline teaching and learning contexts. Indeed, aspects of the pedagogy have been successfully translated to the nursing microbiology study stream at QUT. The aims underpinning the pedagogy are for our students to: (1) Connect scientific theory with scientific practice in a more direct and authentic way, (2) Construct factual knowledge and facilitate a deeper understanding, and (3) Develop and refine their higher order flexible thinking and problem solving skills, both semi-independently and independently. The mindset and role of the teaching staff is critical to this approach since for the strategy to be successful tertiary teachers need to abandon traditional instructional modalities based on one-way information delivery. Face-to-face classroom interactions between students and lecturer enable realisation of pedagogical aims (1), (2) and (3). The strategy we have adopted encourages teachers to view themselves more as expert guides in what is very much a student-focused process of scientific exploration and learning. Specific pedagogical strategies embedded in the authentic learning model we have developed include: (i) interactive lecture-tutorial hybrids or lectorials featuring teacher role-plays as well as class-level question-and-answer sessions, (ii) inclusion of “dry” laboratory activities during lectorials to prepare students for the wet laboratory to follow, (iii) real-world problem-solving exercises conducted during both lectorials and wet laboratory sessions, and (iv) designing class activities and formative assessments that probe a student’s higher order flexible thinking skills. Flexible thinking in this context encompasses analytical, critical, deductive, scientific and professional thinking modes. The strategic approach outlined above is designed to provide multiple opportunities for students to apply principles flexibly according to a given situation or context, to adapt methods of inquiry strategically, to go beyond mechanical application of formulaic approaches, and to as much as possible self-appraise their own thinking and problem solving. The pedagogical tools have been developed within both workplace (real world) and theoretical frameworks. The philosophical core of the pedagogy is a coherent pathway of teaching and learning which we, and many of our students, believe is more conducive to student engagement and active learning in the classroom. Qualitative and quantitative data derived from online and hardcopy evaluations, solicited and unsolicited student and graduate feedback, anecdotal evidence as well as peer review indicate that: (i) our students are engaging with the pedagogy, (ii) a constructivist, authentic-learning approach promotes active learning, and (iii) students are better prepared for workplace transition.

Can active learning principles be applied to the bioscience assessments of nursing students? A review of the literature

- Objectives To explore if active learning principles be applied to nursing bioscience assessments and will this influence student perception of confidence in applying theory to practice? - Design and Data Sources A review of the literature utilising searches of various databases including CINAHL, PUBMED, Google Scholar and Mosby's Journal Index. - Methods The literature search identified research from twenty-six original articles, two electronic books, one published book and one conference proceedings paper. - Results Bioscience has been identified as an area that nurses struggle to learn in tertiary institutions and then apply to clinical practice. A number of problems have been identified and explored that may contribute to this poor understanding and retention. University academics need to be knowledgeable of innovative teaching and assessing modalities that focus on enhancing student learning and address the integration issues associated with the theory practice gap. Increased bioscience education is associated with improved patient outcomes therefore by addressing this “bioscience problem” and improving the integration of bioscience in clinical practice there will subsequently be an improvement in health care outcomes. - Conclusion From the literature several themes were identified. First there are many problems with teaching nursing students bioscience education. These include class sizes, motivation, concentration, delivery mode, lecturer perspectives, student's previous knowledge, anxiety, and a lack of confidence. Among these influences the type of assessment employed by the educator has not been explored or identified as a contributor to student learning specifically in nursing bioscience instruction. Second that educating could be achieved more effectively if active learning principles were applied and the needs and expectations of the student were met. Lastly, assessment influences student retention and the student experience and as such assessment should be congruent with the subject content, align with the learning objectives and be used as a stimulus tool for learning.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.

External knowledge and query strategies in active learning: A study in clinical information extraction

This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.

Web-based active learning and frequent feedback: Engaging first-year university students

Web-based technology is particularly well-suited to promoting active student involvement in the processes of learning. All students enrolled in a first-year educational psychology unit were required to complete ten weekly online quizzes, ten weekly student-generated questions and ten weekly student answers to those questions. Results of an online survey of participating students strongly support the viability and perceived benefits of such an instructional approach. Although students reported that the 30 assessments were useful and reasonable, the most common theme to emerge from the professional reflections of participating lecturers was that the marking of questions and answers was unmanageable.

The introduction of an interactive teaching and learning activity (TLA) in class and its relationship to students’ learning-outcomes

In the university education arena, it is becoming apparent that traditional methods of conducting classes are not the most effective ways to achieve desired learning outcomes. The traditional class/method involves the instructor verbalizing information for passive, note-taking students who are assumed to be empty receptacles waiting to be filled with knowledge. This method is limited in its effectiveness, as the flow of information is usually only in one direction. Furthermore, “It has been demonstrated that students in many cases can recite and apply formulas in numerical problems, but the actual meaning and understanding of the concept behind the formula is not acquired (Crouch & Mazur)”. It is apparent that memorization is the main technique present in this approach. A more effective method of teaching involves increasing the students’ level of activity during, and hence their involvement in the learning process. This technique stimulates self- learning and assists in keeping these students’ levels of concentration more uniform. In this work, I am therefore interested in studying the influence of a particular TLA on students’ learning-outcomes. I want to foster high-level understanding and critical thinking skills using active learning (Silberman, 1996) techniques. The TLA in question aims to promote self-study by students and to expose them to a situation where their learning-outcomes can be tested. The motivation behind this activity is based on studies which suggest that some sensory modalities are more effective than others. Using various instruments for data collection and by means of a thorough analysis I present evidence of the effectiveness of this action research project which aims to improve my own teaching practices, with the ultimate goal of enhancing student’s learning.

Connecting across continents : collaborative learning in a Web 2.0 world

Purpose – The article aims to review a university course, offered to students in both Australia and Germany, to encourage them to learn about designing, implementing, marketing and evaluating information programs and services in order to build active and engaged communities. The concepts and processes of Web 2.0 technologies come together in the learning activities, with students establishing their own personal learning networks (PLNs). Design/methodology/approach – The case study examines the principles of learning and teaching that underpin the course and presents the students' own experiences of the challenges they faced as they explored the interactive, participative and collaborative dimensions of the web. Findings – The online format of the course and the philosophy of learning through play provided students with a safe and supportive environment for them to move outside of their comfort zones, to be creative, to experiment and to develop their professional personas. Reflection on learning was a key component that stressed the value of reflective practice in assisting library and information science (LIS) professionals to adapt confidently to the rapidly changing work environment. Originality/value – This study provides insights into the opportunities for LIS courses to work across geographical boundaries, to allow students to critically appraise library practice in different contexts and to become active participants in wider professional networks.

Effects of introducing an interactive teaching and learning activity (TLA) in the engineering classroom

This research study examines qualitatively and quantitatively the influence of introducing an activity in the traditional engineering classroom. It studies instances of active learning and its relationship with the student learning outcomes. The primary purpose of this study was to compare the learning outcomes of students who were involved in an active TLA with those students who were not, instead they learned under traditional teaching and studying approaches. I present the argument that the introduction of a TLA in class stimulates student engagement bringing enormous benefits to student learning. The outcomes of this study were measured using qualitative and quantitative data to evaluate the levels of student engagement, achievement and satisfaction in the terms of Intended Learning Outcomes (ILOs). Results indicate that students held positive attitude towards the activities in class and also, that a positive link between TLA, learning approach and learning outcome exist. It also provides insights about the potential benefits of active learning when compared with traditional, passive and teacher-centred methods of teaching & learning.

Learning and teaching epidemiology with audience response technology

Background The learning and teaching of epidemiology is core to many public health programs. Many students find the content of epidemiology, and specifically risk of bias assessment, challenging to learn. Howbeit, learning is enhanced when knowledge is able to be acquired from an active-learning, hands-on experience. Methods The innovative use of wireless audience response technology “clickers” was incorporated into the lectures of the university’s post-graduate epidemiology units and the tailored epidemiological modules delivered for professional disciplines (e.g. optometry). Clickers were used to apply several pedagogical approaches of active learning including peer-instruction and real-world simulation. Students were also assessed for their gain in knowledge within the lecture (pre-post) and their perceptions of how the use of clickers helped them learn. The routine university-wide end of semester Insight Survey provided further information of the student’s satisfaction with the approach. Results The technology was useful in identifying deficits of knowledge of key concepts either before or after instruction. Where key concepts were re-tested post-lecture, as expected, knowledge increased significantly and provided immediate feed-back to students. Across the lecture series, typically 85% of students identified the technology helped them learn, increased their opportunity to interact with the lecturer, and recommend their use for future classes. The Insight Survey report identified 93% of respondents identified the unit in which clickers were consistently used provided good learning opportunities. Numerous student comments supported the teaching method. Conclusions Epidemiological subject matter lends itself to incorporation of audience response technology. The use of the technology to facilitate interactive voting provides an instant response and participation of everyone to enhance the classroom experience. The pedagogical approach increases students’ knowledge and increases their satisfaction with the unit.

Fusing shrinking and expanding active contour models for robust IRIS segmentation

The performance of iris recognition systems is significantly affected by the segmentation accuracy, especially in non- ideal iris images. This paper proposes an improved method to localise non-circular iris images quickly and accurately. Shrinking and expanding active contour methods are consolidated when localising inner and outer iris boundaries. First, the pupil region is roughly estimated based on histogram thresholding and morphological operations. There- after, a shrinking active contour model is used to precisely locate the inner iris boundary. Finally, the estimated inner iris boundary is used as an initial contour for an expanding active contour scheme to find the outer iris boundary. The proposed scheme is robust in finding exact the iris boundaries of non-circular and off-angle irises. In addition, occlusions of the iris images from eyelids and eyelashes are automatically excluded from the detected iris region. Experimental results on CASIA v3.0 iris databases indicate the accuracy of proposed technique.

Sequential nonlinear manifold learning

The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.