Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Facial Nerve Image Enhancement from CBCT using Supervised Learning Technique

Facial nerve segmentation plays an important role in surgical planning of cochlear implantation. Clinically available CBCT images are used for surgical planning. However, its relatively low resolution renders the identification of the facial nerve difficult. In this work, we present a supervised learning approach to enhance facial nerve image information from CBCT. A supervised learning approach based on multi-output random forest was employed to learn the mapping between CBCT and micro-CT images. Evaluation was performed qualitatively and quantitatively by using the predicted image as input for a previously published dedicated facial nerve segmentation, and cochlear implantation surgical planning software, OtoPlan. Results show the potential of the proposed approach to improve facial nerve image quality as imaged by CBCT and to leverage its segmentation using OtoPlan.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

Learning from failure--rationale and design for a study about discontinuation of randomized trials (DISCO study)

Background Randomized controlled trials (RCTs) may be discontinued because of apparent harm, benefit, or futility. Other RCTs are discontinued early because of insufficient recruitment. Trial discontinuation has ethical implications, because participants consent on the premise of contributing to new medical knowledge, Research Ethics Committees (RECs) spend considerable effort reviewing study protocols, and limited resources for conducting research are wasted. Currently, little is known regarding the frequency and characteristics of discontinued RCTs. Methods/Design Our aims are, first, to determine the prevalence of RCT discontinuation for specific reasons; second, to determine whether the risk of RCT discontinuation for specific reasons differs between investigator- and industry-initiated RCTs; third, to identify risk factors for RCT discontinuation due to insufficient recruitment; fourth, to determine at what stage RCTs are discontinued; and fifth, to examine the publication history of discontinued RCTs. We are currently assembling a multicenter cohort of RCTs based on protocols approved between 2000 and 2002/3 by 6 RECs in Switzerland, Germany, and Canada. We are extracting data on RCT characteristics and planned recruitment for all included protocols. Completion and publication status is determined using information from correspondence between investigators and RECs, publications identified through literature searches, or by contacting the investigators. We will use multivariable regression models to identify risk factors for trial discontinuation due to insufficient recruitment. We aim to include over 1000 RCTs of which an anticipated 150 will have been discontinued due to insufficient recruitment. Discussion Our study will provide insights into the prevalence and characteristics of RCTs that were discontinued. Effective recruitment strategies and the anticipation of problems are key issues in the planning and evaluation of trials by investigators, Clinical Trial Units, RECs and funding agencies. Identification and modification of barriers to successful study completion at an early stage could help to reduce the risk of trial discontinuation, save limited resources, and enable RCTs to better meet their ethical requirements.

Learning styles vary among general surgery residents: analysis of 12 years of data

PURPOSE: Understanding the learning styles of individuals may assist in the tailoring of an educational program to optimize learning. General surgery faculty and residents have been characterized previously as having a tendency toward particular learning styles. We seek to understand better the learning styles of general surgery residents and differences that may exist within the population. METHODS: The Kolb Learning Style Inventory was administered yearly to general surgery residents at the University of Cincinnati from 1994 to 2006. This tool allows characterization of learning styles into 4 groups: converging, accommodating, assimilating, and diverging. The converging learning style involves education by actively solving problems. The accommodating learning style uses emotion and interpersonal relationships. The assimilating learning style learns by abstract logic. The diverging learning style learns best by observation. Chi-square analysis and analysis of variance were performed to determine significance. RESULTS: Surveys from 1994 to 2006 (91 residents, 325 responses) were analyzed. The prevalent learning style was converging (185, 57%), followed by assimilating (58, 18%), accommodating (44, 14%), and diverging (38, 12%). At the PGY 1 and 2 levels, male and female residents differed in learning style, with the accommodating learning style being relatively more frequent in women and assimilating learning style more frequent in men (Table 1, p < or = 0.001, chi-square test). Interestingly, learning style did not seem to change with advancing PGY level within the program, which suggests that individual learning styles may be constant throughout residency training. If a resident's learning style changed, it tended to be to converging. In addition, no relation exists between learning style and participation in dedicated basic science training or performance on the ABSIT/SBSE. CONCLUSIONS: Our data suggests that learning style differs between male and female general surgery residents but not with PGY level or ABSIT/SBSE performance. A greater understanding of individual learning styles may allow more refinement and tailoring of surgical programs.

Cerebellar disorders in childhood: cognitive problems

Over the last decade, increasing evidence of cognitive functions of the cerebellum during development and learning processes could be ascertained. Posterior fossa malformations such as cerebellar hypoplasia or Joubert syndrome are known to be related to developmental problems in a marked to moderate extent. More detailed analyses reveal special deficits in attention, processing speed, visuospatial functions, and language. A study about Dandy Walker syndrome states a relationship of abnormalities in vermis lobulation with developmental problems. Further lobulation or volume abnormalities of the cerebellum and/or vermis can be detected in disorders as fragile X syndrome, Downs's syndrome, William's syndrome, and autism. Neuropsychological studies reveal a relation of dyslexia and attention deficit disorder with cerebellar functions. These functional studies are supported by structural abnormalities in neuroimaging in these disorders. Acquired cerebellar or vermis atrophy was found in groups of children with developmental problems such as prenatal alcohol exposure or extreme prematurity. Also, focal lesions during childhood or adolescence such as cerebellar tumor or stroke are related with neuropsychological abnormalities, which are most pronounced in visuospatial, language, and memory functions. In addition, cerebellar atrophy was shown to be a bad prognostic factor considering cognitive outcome in children after brain trauma and leukemia. In ataxia teleangiectasia, a neurodegenerative disorder affecting primarily the cerebellar cortex, a reduced verbal intelligence quotient and problems of judgment of duration are a hint of the importance of the cerebellum in cognition. In conclusion, the cerebellum seems to play an important role in many higher cognitive functions, especially in learning. There is a suggestion that the earlier the incorrect influence, the more pronounced the problems.

Defining Goals and Learning Objectives for a Longitudinal Clerkship in the Complex Context of Health Care

In autumn 2007 the Swiss Medical School of Berne (Switzerland) implemented mandatory short-term clerkships in primary health care for all undergraduate medical students. Students studying for a Bachelor degree complete 8 half-days per year in the office of a general practitioner, while students studying for a Masters complete a three-week clerkship. Every student completes his clerkships in the same GP office during his four years of study. The purpose of this paper is to show how the goals and learning objectives were developed and evaluated. Method:A working group of general practitioners and faculty had the task of defining goals and learning objectives for a specific training program within the complex context of primary health care. The group based its work on various national and international publications. An evaluation of the program, a list of minimum requirements for the clerkships, an oral exam in the first year and an OSCE assignment in the third year assessed achievement of the learning objectives. Results: The findings present the goals and principal learning objectives for these clerkships, the results of the evaluation and the achievement of minimum requirements. Most of the defined learning objectives were taught and duly learned by students. Some learning objectives proved to be incompatible in the context of ambulatory primary care and had to be adjusted accordingly. Discussion: The learning objectives were evaluated and adapted to address students’ and teachers’ needs and the requirements of the medical school. The achievement of minimum requirements (and hence of the learning objectives) for clerkships has been mandatory since 2008. Further evaluations will show whether additional learning objectives need to be adopte

Learning by the Dendritic Prediction of Somatic Spiking

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms.

An innovative blended learning approach using virtual patients as preparation for skills laboratory training: perceptions of students and tutors

BACKGROUND Currently only a few reports exist on how to prepare medical students for skills laboratory training. We investigated how students and tutors perceive a blended learning approach using virtual patients (VPs) as preparation for skills training. METHODS Fifth-year medical students (N=617) were invited to voluntarily participate in a paediatric skills laboratory with four specially designed VPs as preparation. The cases focused on procedures in the laboratory using interactive questions, static and interactive images, and video clips. All students were asked to assess the VP design. After participating in the skills laboratory 310 of the 617 students were additionally asked to assess the blended learning approach through established questionnaires. Tutors' perceptions (N=9) were assessed by semi-structured interviews. RESULTS From the 617 students 1,459 VP design questionnaires were returned (59.1%). Of the 310 students 213 chose to participate in the skills laboratory; 179 blended learning questionnaires were returned (84.0%). Students provided high overall acceptance ratings of the VP design and blended learning approach. By using VPs as preparation, skills laboratory time was felt to be used more effectively. Tutors perceived students as being well prepared for the skills laboratory with efficient uses of time. CONCLUSION The overall acceptance of the blended learning approach was high among students and tutors. VPs proved to be a convenient cognitive preparation tool for skills training.

When language of instruction and language of application differ: Cognitive costs of bilingual mathematics learning

Bilingual education programs implicitly assume that the acquired knowledge is represented in a language-independent way. This assumption, however, stands in strong contrast to research findings showing that information may be represented in a way closely tied to the specific language of instruction and learning. The present study aims to examine whether and to which extent cognitive costs appear during arithmetic learning when language of instruction and language of retrieving differ. Thirty-nine high school students participating in a bilingual education program underwent a four-day training on multiplication and subtraction problems in one language (German or French), followed by a test session in which they had to solve trained as well as untrained problems in both languages. We found that cognitive costs related to language switching appeared for both arithmetic operations. Implications of our findings are discussed with respect to bilingual education as well as to cognitive mechanisms underlying different arithmetic operations.

Forget about theory - practice is all? - Student teachers' learning in practicum

In 1999, all student teachers at secondary I level at the University of Bern who had to undertake an internship were asked to participate in a study on learning processes during practicum: 150 students and their mentors in three types of practicum participated—introductory practicum (after the first half‐year of studies), intermediate practicum (after two years of studies) and final practicum (after three years of studies). At the end of the practicum, student teachers and mentors completed questionnaires on preparing, teaching and post‐processing lessons. All student teachers, additionally, rated their professional skills and aspects of personality (attitudes towards pupils, self‐assuredness and well‐being) before and after the practicum. Forty‐six student teachers wrote daily semi‐structured diaries about essential learning situations during their practicum. Results indicate that in each practicum students improved significantly in preparing, conducting and post‐processing lessons. The mentors rated these changes as being greater than did the student teachers. From the perspective of the student teachers their general teaching skills also improved, and their attitudes toward pupils became more open. Furthermore, during practicum their self‐esteem and subjective well‐being increased. Diary data confirmed that there are no differences between different levels of practicum in terms of learning outcomes, but give some first insight into different ways of learning during internship.

Probleme der Pharmakotherapie in der Hausarztpraxis : Pharmakotherapie konkret - Ein E-Learning für Medizinstudierende

Hintergrund Fehler in der Pharmakotherapie sind häufig und betreffen wahrscheinlich etwa 2-10% aller Verschreibungen. Direkt nach Abschluss des Studiums beschreibt sich nur eine Minderheit der jungen Ärzte als „kompetent zu Verordnen“. Unser Ziel ist es, die Medizinstudierenden in Ergänzung zu den Vorlesungen optimal auf die klinische Tätigkeit des Medikamente Verordnens vorzubereiten. Bereits umgesetzt sind die beiden blended learning Module „Arzneimittelrezepte korrekt schreiben“ und „Polypharmazie im Alter“.

Livelihood and Community Development: LforS learning and simulation game

Up to 15 people can participate in the game, which is supervised by a moderator. Households consisting of 1-5 people discuss options for diversification of household strategies. Aim of the game: By devising appropriate strategies, households seek to stand up to various types of events while improving their economic and social situation and, at the same time, taking account of ecological conditions. The annual General Community Meeting (GCM) provides an opportunity for households to create a general set-up at the local level that is more or less favourable to the strategies they are pursuing. The development of a community investment strategy, to be implemented by the GCM, and successful coordination between households will allow players to optimise their investments at the household level. The household who owns the most assets at the end of the game wins. Players participate very actively, as the game stimulates lively and interesting discussions. They find themselves confronted with different types of decision-making related to the reality of their daily lives. They explore different ways to model their own household strategies and discuss risks and opportunities. Reflections on the course of the game continually refer to the real-life situations of the participants.