scholarly journals A deep learning approach for identifying biomedical breakthrough discoveries using context analysis

2021 ◽  
Author(s):  
Xue Wang ◽  
Xuemei Yang ◽  
Jian Du ◽  
Xuwen Wang ◽  
Jiao Li ◽  
...  
Keyword(s):  
Evaluation Process ◽  
Automatic Identification ◽  
Learning Approach ◽  
Research Papers ◽  
Context Analysis ◽  
Self Evaluation ◽  
Major Development ◽  
Cue Words ◽  
Scientific Fields ◽  
Identification Model

AbstractBreakthrough research in scientific fields usually comes as a manifestation of major development and advancement. These advances build to an epiphany where new ways of thinking about a problem become possible. Identifying breakthrough research can be useful for cultivating and funding further innovation. This article presents a new method for identifying scientific breakthroughs from research papers based on cue words commonly associated with major advancements. We looked for specific terms signifying scientific breakthroughs in citing sentences to identify breakthrough articles. By setting a threshold for the number of citing sentences (“citances”) with breakthrough cue words that peer scholars often use when evaluating research, we identified articles containing breakthrough research. We call this approach the “others-evaluation” process. We then shortlisted candidates from the selected articles based on the authors’ evaluations of their own research, found in the abstracts. This we call the “self-evaluation” process. Combining the two approaches into a dual “others-self” evaluation process, we arrived at a sample of 237 potential breakthrough articles, most of which are recommended by the Faculty Opinions. Based on the breakthrough articles identified, using SVM, TextCNN, and BERT to train the models to identify abstracts with breakthrough evaluations. This automatic identification model can greatly simplify the process of others-self-evaluation process and promote identifying breakthrough research.

scholarly journals A Deep Learning Approach for the Automatic Identification of the Left Atrium Within CT Scans

2019 ◽  
Author(s):  
Alex Deakyne ◽  
Erik Gaasedelen ◽  
Paul A. Iaizzo
Keyword(s):  
Deep Learning ◽  
Left Atrium ◽  
Feature Detection ◽  
Ct Scans ◽  
Automatic Identification ◽  
Learning Approach ◽  
Anatomical Features ◽  
Major Development ◽  
Bounding Boxes ◽  
Single Neural Network

Recent advancements in deep learning have led to the possibility of increased performance in computer vision tools. A major development has been the usage of Convolutional Neural Networks (CNN) for automatically detecting features within a given image. Architectures such as YOLO1 have obtained incredibly high performances for the real-time detection of every-day objects within images. However to date, there have been few reports of deep learning applied to detect anatomical features within CT scans; especially those within the cardiovascular space. We propose here an automatic anatomical feature detection pipeline for identifying the features of the left atrium using a CNN. Slices of CT scans were fed into a single neural network which predicted the four bounding box coordinates that encapsulate the left atrium. The network can be optimized end-to-end and generate predictions at great speed, achieving a validation smooth L1 loss of 11.95 when predicting the left atrial bounding boxes.

A regulatory focus approach to the self evaluation process

2005 ◽  
Author(s):  
Geoffrey Leonardelli ◽  
Jessica Lakin ◽  
Robert Arkin
Keyword(s):  
Regulatory Focus ◽  
Evaluation Process ◽  
The Self ◽  
Self Evaluation

The ideal self is me: Deconstructing the self-evaluation process

2011 ◽  
Author(s):  
Corey L. Guenther ◽  
Kathryn Applegate ◽  
Steven Svoboda ◽  
Emily Adams
Keyword(s):  
Evaluation Process ◽  
The Self ◽  
Ideal Self ◽  
Self Evaluation ◽  
The Ideal

Leadership and school self-evaluation in Irish-medium immersion: A roadmap for success

2021 ◽  
pp. 174114322110152
Author(s):  
TJ Ó Ceallaigh ◽  
Aoife Ní Shéaghdha
Keyword(s):  
Quality Indicators ◽  
Cognitive Skills ◽  
Best Practice ◽  
Research Question ◽  
Evaluation Process ◽  
Successful Implementation ◽  
Language And Literacy ◽  
Evaluation Tool ◽  
Self Evaluation ◽  
Individual Interviews

While research on Irish-medium immersion education (IME) has heralded benefits such as cognitive skills, academic achievement and language and literacy development, many studies have also identified challenges to its successful implementation. Immersion-specific research-validated tools can help school leaders navigate the school self-evaluation journey, critically review and evaluate the quality of aspects of their school’s provision and plan for improvement. This paper reports on one theme, leadership, from a larger study, Quality indicators of best practice in Irish-medium immersion (Ó Ceallaigh and Ní Shéaghdha, 2017). Qualitative in nature, the study was guided by the following research question: What are IME educators’ perceptions of best practices in IME?. The study explored 120 IME educators’ perceptions of best practice in IME to inform the development of IME quality indicators. Individual interviews and focus group interviews were utilised to collect data. Data analysis revealed particular themes related to best IME leadership practices. Findings in turn informed the design of an evidence-informed school self-evaluation tool for IME settings. The various functions of the tool will be explored with a particular emphasis on building teaching and leadership capacity in IME through the school self-evaluation process.

The Female Physique: Motives Guiding Self-Evaluation

2004 ◽  
Vol 13 (2) ◽  
pp. 5-16
Author(s):  
Carolyn Vos Strache ◽  
Alana Strong ◽  
Cheree Peterson
Keyword(s):  
Southern California ◽  
Evaluation Process ◽  
The Self ◽  
Physical Aspect ◽  
Individual Response ◽  
Structured Interviews ◽  
Chi Square ◽  
Self Evaluation ◽  
Significant Measure ◽  
Chi Square Analysis

The omnipresent physical self remains for young adult females a significant measure of self-worth. Therefore, it comes as no surprise that coping strategies are as complex as they are pervasive as young women strive to maintain positive psychological outlooks despite negatively-perceived physical attributes. Self-presentational concerns may affect one’s activity choice.This study expands on the work of Taylor, Neter, and Wayment (1995) to determine which motives guide the self-evaluation processes of the physical self. An examination of structured interviews identifies which motives direct women in the self-evaluation of their bodies, and concurrently examines whether different motives determine individual response when appraising a “good” versus “not good” physical aspect. Motives, as defined by Taylor et al. (1995), were self-enhancement, self-verification, self-improvement and self-assessment. Interviews were conducted with 30 female, Southern California, undergraduate college students from Southern California, ranging in age from 19-22.A chi-square analysis revealed that women employed different motives in “good” versus “not good” body aspect comparisons (Enhancement: X2 = 21.78 p< .01; Verification: X2 = 10.05 p< .01; Improvement: X2 = 5.15 p< .05). When describing a “good” aspect, women employed the enhancement motive 92 percent of the time, verification 80 percent of the time, and improvement 15 percent of the time. For “not good” aspects, women used enhancement motive 53 percent of the time, verification 98 percent of the time, and improvement 33 percent of the time. Women used more than one motive 74 percent of the time and single motives only 26 percent of the time in the evaluation process. Direct quotes reveal that almost all the women sought out information about themselves when they thought it would reflect favorably. However, when they reported on a “not good” aspect, coping mechanisms included redirecting their attention to more positive characteristics or mentally cordoning off an area of weakness to prevent that attribute from permeating all aspects of their identity. Understanding how we think in the self-evaluation process may offer an explanation why some people are motivated to exercise and why others are not.

A deep learning approach for automatic identification of subsea events using AUV data

2020 ◽  
Vol 20 (2020) ◽  
pp. 370-371
Author(s):  
Marcelo Igor Lourenço De Souza ◽  
Jean David Job Emmanuel Marie Caprace ◽  
Ramiro Fernandes Ramos ◽  
João Vitor Marques de Oliveira Moita ◽  
Luisa Nogueira de Azeredo Coutinho Soares ◽  
...  
Keyword(s):  
Deep Learning ◽  
Automatic Identification ◽  
Learning Approach

Deep Learning-Based Classification of Malignant and Benign Cells in Dermatoscopic Images via Transfer Learning Approach

2021 ◽  
Author(s):  
V. Akash Kumar ◽  
Vijaya Mishra ◽  
Monika Arora
Keyword(s):  
Skin Cancer ◽  
Transfer Learning ◽  
Human Life ◽  
Skin Pigmentation ◽  
Automatic Identification ◽  
Learning Approach ◽  
Predicted Model ◽  
Classification Tasks ◽  
Cancerous Cells

The inhibition of healthy cells creating improper controlling process of the human body system indicates the occurrence of growth of cancerous cells. The cluster of such cells leads to the development of tumor. The observation of this type of abnormal skin pigmentation is done using an effective tool called Dermoscopy. However, these dermatoscopic images possess a great challenge for diagnosis. Considering the characteristics of dermatoscopic images, transfer learning is an appropriate approach of automatically classifying the images based on the respective categories. An automatic identification of skin cancer not only saves human life but also helps in detecting its growth at an earlier stage which saves medical practitioner’s effort and time. A newly predicted model has been proposed for classifying the skin cancer as benign or malignant by DCNN with transfer learning and its pre-trained models such as VGG 16, VGG 19, ResNet 50, ResNet 101, and Inception V3. The proposed methodology aims at examining the efficiency of pre-trained models and transfer learning approach for the classification tasks and opens new dimensions of research in the field of medicines using imaging technique which can be implementable in real-time applications.

scholarly journals Analysis and Design of Data Warehouse on Academic STMIK STIKOM Bali

2017 ◽  
Vol 2 (1) ◽  
pp. 35
Author(s):  
Komang Budiarta ◽  
Putu Agung Ananta Wijaya ◽  
Cokorde Gede Indra Partha
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Evaluation Process ◽  
Process Data ◽  
Study Program ◽  
Analysis And Design ◽  
Self Evaluation ◽  
Data Source ◽  
System Information

College accreditation by BAN-PT is one of the parameters in determining the quality of universities in Indonesia. As consideration to achieve the standard from BAN-PT, so they have an evaluation process itself in study program or college to be meet the standard universities when set by the BAN-PT. In carrying out the process of self evaluation, required data source that is used as the basis in assessing on a criteria. In most of the study program, all data spread on the system information and physical document that different, that is require more time and effort to integrate up to interpret. Data warehouse fight important in collecting data that spread and become an information. The process data warehouse with ETL used to integrate, extract, clean, transforming and reload into the data warehouse. With the existence of the data warehouse on Academic STIMIK STIKOM Bali can make it easier for executives to get the information to support the standard accreditation standart three and can be used as a reference in decision making.

scholarly journals Using Blended Learning Approach (BLA) in Inclusive Education Course: A Study Investigating Teacher Students’ Perception

2020 ◽  
Vol 15 (02) ◽  
pp. 72 ◽  
Author(s):  
Rasmitadila Rasmitadila ◽  
Widyasari Widyasari ◽  
Megan Asri Humaira ◽  
Anna Riana Suryanti Tambunan ◽  
Reza Rachmadtullah ◽  
...  
Keyword(s):  
Blended Learning ◽  
Student Perceptions ◽  
Inclusive Education ◽  
Learning Approach ◽  
Positive Perception ◽  
Context Analysis ◽  
Analysis Techniques ◽  
Teacher Students ◽  
Learning Interest ◽  
The Web

The purpose of this research is to explore the students’ perception about the implementation of blended learning approach (BLA) in inclusive education course. Thirty (30) students participated in this research. The data collection was done by open interview to know students’ perception about the implementation of blended learning. The interview results were analyzed using context analysis techniques. Based on the data analysis, there are four catego-ries of students' attention, namely: display of learning management system (LMS); accessibility; the benefits and sustainability. Student perceptions of each category are: the LMS display on the web of 50.53% is appropriate and simple, but must be modified to make it easier for students to understand. The negative perception about accessibility of 69.57% indicates that internet access to the web is still unstable and slow. Positive perception about BLA benefit of 66.94% indicates good benefits to students especially in terms of adding learn-ing experiences, knowledge, variations of learning models and learning more flexible and independent. A positive perception of BLA sustainability of 66.18% indicates should be continued because it can increase students' learning interest, learn more modern, flexible and independent.

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