scholarly journals A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Mujiono Sadikin ◽  
Mohamad Ivan Fanany ◽  
T. Basaruddin
Keyword(s):  
State Of The Art ◽  
Data Representation ◽  
Training Data ◽  
The Third ◽  
Single Drug ◽  
Medical Text ◽  
Name Entity ◽  
Wide Range ◽  
New Treatment ◽  
Representation Techniques

One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of new terms addition, a wide range of name variation for the same drug, the lack of labeled dataset sources and external knowledge, and the multiple token representations for a single drug name. Although many approaches have been proposed to overwhelm the task, some problems remained with poor F-score performance (less than 0.75). This paper presents a new treatment in data representation techniques to overcome some of those challenges. We propose three data representation techniques based on the characteristics of word distribution and word similarities as a result of word embedding training. The first technique is evaluated with the standard NN model, that is, MLP. The second technique involves two deep network classifiers, that is, DBN and SAE. The third technique represents the sentence as a sequence that is evaluated with a recurrent NN model, that is, LSTM. In extracting the drug name entities, the third technique gives the best F-score performance compared to the state of the art, with its average F-score being 0.8645.

Global tests for novelty

2015 ◽  
Vol 26 (4) ◽  
pp. 1867-1880
Author(s):  
Ilmari Ahonen ◽  
Denis Larocque ◽  
Jaakko Nevalainen
Keyword(s):  
Novelty Detection ◽  
Null Distribution ◽  
Real Data ◽  
Training Data ◽  
Data Sets ◽  
Screening Experiments ◽  
Wide Range ◽  
Global Tests ◽  
New Treatment ◽  
The Individual

Outlier detection covers the wide range of methods aiming at identifying observations that are considered unusual. Novelty detection, on the other hand, seeks observations among newly generated test data that are exceptional compared with previously observed training data. In many applications, the general existence of novelty is of more interest than identifying the individual novel observations. For instance, in high-throughput cancer treatment screening experiments, it is meaningful to test whether any new treatment effects are seen compared with existing compounds. Here, we present hypothesis tests for such global level novelty. The problem is approached through a set of very general assumptions, making it innovative in relation to the current literature. We introduce test statistics capable of detecting novelty. They operate on local neighborhoods and their null distribution is obtained by the permutation principle. We show that they are valid and able to find different types of novelty, e.g. location and scale alternatives. The performance of the methods is assessed with simulations and with applications to real data sets.

Introduction: Rethinking Career Development

2021 ◽  
Author(s):  
Phil McCash ◽  
Tristram Hooley ◽  
Peter J. Robertson
Keyword(s):  
Career Development ◽  
Government Policy ◽  
Group Work ◽  
State Of The Art ◽  
Course Development ◽  
The Third ◽  
Wide Range ◽  
Life Course Development ◽  
The Rich ◽  
Selection Of

This chapter introduces readers to The Oxford Handbook of Career Development and to the field of career development. The origins of the field are discussed in relation to vocational guidance, differential psychology, interactionist sociology, and life course development. The selection of the term career development for this volume is explained with regard to three interlocking themes: the broader contexts of career development, including government policy; the wide range of theory concerned with career-related experiences, phenomena, and behaviour; and the broad spectrum of career helping practices, including one-to-one work and group work. The inspiration and aims for the volume are set out, and the challenges associated with terminology in the field are acknowledged. The editors seek to provide a state-of-the-art reference point for the field of career development, and engender a transdisciplinary and international dialogue that explores key current ideas, debates, and controversies. The volume is divided into three sections. The first explores the economic, educational, and public policy contexts for practice. The second section focuses on concepts and explores the rich theoretical landscape of the field. The third section turns to practice, and the translation of ideas into action to support individuals and groups with their career development.

Health Informatics Education in the Third World

1989 ◽  
Vol 28 (04) ◽  
pp. 270-272 ◽  
Author(s):  
O. Rienhoff
Keyword(s):  
Developing Countries ◽  
Health Informatics ◽  
Third World ◽  
State Of The Art ◽  
The State ◽  
Collaboration Network ◽  
Educational Tools ◽  
The Third ◽  
The Third World

Abstract:The state of the art is summarized showing many efforts but only few results which can serve as demonstration examples for developing countries. Education in health informatics in developing countries is still mainly dealing with the type of health informatics known from the industrialized world. Educational tools or curricula geared to the matter of development are rarely to be found. Some WHO activities suggest that it is time for a collaboration network to derive tools and curricula within the next decade.

The Colonial Documentary Film in South and South-East Asia

2017 ◽  
Keyword(s):  
East Asia ◽  
Subject Matter ◽  
Documentary Film ◽  
East Asian ◽  
South East Asia ◽  
Post Colonial ◽  
Historical Perspectives ◽  
The Third ◽  
Wide Range ◽  
Global Understanding

Writing from a wide range of historical perspectives, contributors to the anthology shed new light on historical, theoretical and empirical issues pertaining to the documentary film, in order to better comprehend the significant transformations of the form in colonial, late colonial and immediate post-colonial and postcolonial times in South and South-East Asia. In doing so, this anthology addresses an important gap in the global understanding of documentary discourses, practices, uses and styles. Based upon in-depth essays written by international authorities in the field and cutting-edge doctoral projects, this anthology is the first to encompass different periods, national contexts, subject matter and style in order to address important and also relatively little-known issues in colonial documentary film in the South and South-East Asian regions. This anthology is divided into three main thematic sections, each of which crosses national or geographical boundaries. The first section addresses issues of colonialism, late colonialism and independence. The second section looks at the use of the documentary film by missionaries and Christian evangelists, whilst the third explores the relation between documentary film, nationalism and representation.

CLINICAL AND FORENSIC ASPECTS OF PHARMACOBEZOARS

2020 ◽  
Vol 12 ◽  
Author(s):  
Francisco Basílio ◽  
Ricardo Jorge Dinis-Oliveira
Keyword(s):  
State Of The Art ◽  
Signs And Symptoms ◽  
Immediate Release ◽  
Diagnosis And Treatment ◽  
Blood Concentrations ◽  
Forensic Practice ◽  
Wide Range ◽  
Therapeutic Doses ◽  
Complete History ◽  
Lethal Blood

Background: Pharmacobezoars are specific types of bezoars formed when medicines, such as tablets, suspensions, and/or drug delivery systems, aggregate and may cause death by occluding airways with tenacious material or by eluting drugs resulting in toxic or lethal blood concentrations. Objective: This work aims to fully review the state-of-the-art regarding pathophysiology, diagnosis, treatment and other relevant clinical and forensic features of pharmacobezoars. Results: patients of a wide range of ages and in both sexes present with signs and symptoms of intoxications or more commonly gastrointestinal obstructions. The exact mechanisms of pharmacobezoar formation are unknown but is likely multifactorial. The diagnosis and treatment depend on the gastrointestinal segment affected and should be personalized to the medication and the underlying factor. A good and complete history, physical examination, image tests, upper endoscopy and surgery through laparotomy of the lower tract are useful for diagnosis and treatment. Conclusion: Pharmacobezoars are rarely seen in clinical and forensic practice. They are related to controlled or immediate-release formulations, liquid or non-digestible substances, in normal or altered digestive motility/anatomy tract, and in overdoses or therapeutic doses, and should be suspected in the presence of risk factors or patients taking drugs which may form pharmacobezoars.

Computers in Geology - 25 Years of Progress

1994 ◽  
Keyword(s):  
Computer Modeling ◽  
Quantitative Methods ◽  
State Of The Art ◽  
International Association ◽  
Mathematical Geology ◽  
25Th Anniversary ◽  
The Earth ◽  
Wide Range ◽  
History Of ◽  
Mapping Techniques

This volume vividly demonstrates the importance and increasing breadth of quantitative methods in the earth sciences. With contributions from an international cast of leading practitioners, chapters cover a wide range of state-of-the-art methods and applications, including computer modeling and mapping techniques. Many chapters also contain reviews and extensive bibliographies which serve to make this an invaluable introduction to the entire field. In addition to its detailed presentations, the book includes chapters on the history of geomathematics and on R.G.V. Eigen, the "father" of mathematical geology. Written to commemorate the 25th anniversary of the International Association for Mathematical Geology, the book will be sought after by both practitioners and researchers in all branches of geology.

Duoethnography: A Polytheoretical Approach to (Re)Storing, (Re)Storying the Meanings That One Gives

2020 ◽  
pp. 396-423
Author(s):  
John Joseph Norris ◽  
Richard D. Sawyer
Keyword(s):  
Social Justice ◽  
Critical Theory ◽  
Third Space ◽  
The Third ◽  
The Core ◽  
Wide Range ◽  
Core Elements ◽  
Feminist Inquiry

This chapter summarizes the advancement of duoethnography throughout its fifteen-year history, employing examples from a variety of topics in education and social justice to provide a wide range of approaches that one may take when conducting a duoethnography. A checklist articulates what its cofounders consider the core elements of duoethnographies, additional features that may or may not be employed and how some studies purporting to be duoethnographies may not be so. The chapter indicates connections between duoethnography and a number of methodological concepts including the third space, the problematics of representation, feminist inquiry, and critical theory using published examples by several duoethnographers.

scholarly journals Improving Semi-Supervised Learning for Audio Classification with FixMatch

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1807
Author(s):  
Sascha Grollmisch ◽  
Estefanía Cano
Keyword(s):  
Neural Networks ◽  
Supervised Learning ◽  
Transfer Learning ◽  
Data Transfer ◽  
State Of The Art ◽  
Training Data ◽  
Audio Classification ◽  
Image Domain ◽  
Full Dataset ◽  
Audio Data

Including unlabeled data in the training process of neural networks using Semi-Supervised Learning (SSL) has shown impressive results in the image domain, where state-of-the-art results were obtained with only a fraction of the labeled data. The commonality between recent SSL methods is that they strongly rely on the augmentation of unannotated data. This is vastly unexplored for audio data. In this work, SSL using the state-of-the-art FixMatch approach is evaluated on three audio classification tasks, including music, industrial sounds, and acoustic scenes. The performance of FixMatch is compared to Convolutional Neural Networks (CNN) trained from scratch, Transfer Learning, and SSL using the Mean Teacher approach. Additionally, a simple yet effective approach for selecting suitable augmentation methods for FixMatch is introduced. FixMatch with the proposed modifications always outperformed Mean Teacher and the CNNs trained from scratch. For the industrial sounds and music datasets, the CNN baseline performance using the full dataset was reached with less than 5% of the initial training data, demonstrating the potential of recent SSL methods for audio data. Transfer Learning outperformed FixMatch only for the most challenging dataset from acoustic scene classification, showing that there is still room for improvement.

scholarly journals Transcription Alignment of Historical Vietnamese Manuscripts without Human-Annotated Learning Samples

2021 ◽  
Vol 11 (11) ◽  
pp. 4894
Author(s):  
Anna Scius-Bertrand ◽  
Michael Jungo ◽  
Beat Wolf ◽  
Andreas Fischer ◽  
Marc Bui
Keyword(s):  
Object Detection ◽  
State Of The Art ◽  
Positive Impact ◽  
Detection System ◽  
Training Data ◽  
Detection Accuracy ◽  
Current State ◽  
Alignment Task ◽  
Scanned Image ◽  
Automatic Transcription

The current state of the art for automatic transcription of historical manuscripts is typically limited by the requirement of human-annotated learning samples, which are are necessary to train specific machine learning models for specific languages and scripts. Transcription alignment is a simpler task that aims to find a correspondence between text in the scanned image and its existing Unicode counterpart, a correspondence which can then be used as training data. The alignment task can be approached with heuristic methods dedicated to certain types of manuscripts, or with weakly trained systems reducing the required amount of annotations. In this article, we propose a novel learning-based alignment method based on fully convolutional object detection that does not require any human annotation at all. Instead, the object detection system is initially trained on synthetic printed pages using a font and then adapted to the real manuscripts by means of self-training. On a dataset of historical Vietnamese handwriting, we demonstrate the feasibility of annotation-free alignment as well as the positive impact of self-training on the character detection accuracy, reaching a detection accuracy of 96.4% with a YOLOv5m model without using any human annotation.

scholarly journals Utterance Level Feature Aggregation with Deep Metric Learning for Speech Emotion Recognition

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4233
Author(s):  
Bogdan Mocanu ◽  
Ruxandra Tapu ◽  
Titus Zaharia
Keyword(s):  
Emotion Recognition ◽  
Loss Function ◽  
State Of The Art ◽  
Disease Diagnosis ◽  
Data Representation ◽  
Speech Emotion Recognition ◽  
Audio Features ◽  
Global Accuracy ◽  
Space Data ◽  
Art Techniques

Emotion is a form of high-level paralinguistic information that is intrinsically conveyed by human speech. Automatic speech emotion recognition is an essential challenge for various applications; including mental disease diagnosis; audio surveillance; human behavior understanding; e-learning and human–machine/robot interaction. In this paper, we introduce a novel speech emotion recognition method, based on the Squeeze and Excitation ResNet (SE-ResNet) model and fed with spectrogram inputs. In order to overcome the limitations of the state-of-the-art techniques, which fail in providing a robust feature representation at the utterance level, the CNN architecture is extended with a trainable discriminative GhostVLAD clustering layer that aggregates the audio features into compact, single-utterance vector representation. In addition, an end-to-end neural embedding approach is introduced, based on an emotionally constrained triplet loss function. The loss function integrates the relations between the various emotional patterns and thus improves the latent space data representation. The proposed methodology achieves 83.35% and 64.92% global accuracy rates on the RAVDESS and CREMA-D publicly available datasets, respectively. When compared with the results provided by human observers, the gains in global accuracy scores are superior to 24%. Finally, the objective comparative evaluation with state-of-the-art techniques demonstrates accuracy gains of more than 3%.

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