The Role of Affective Factors in Computer-Aided Musical Learning for Non-musician Adults

Author(s):  
Saebyul Park ◽  
Chung-Kon Shi ◽  
Jeounghoon Kim
2021 ◽  
Vol 14 ◽  
pp. 263177452199305
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Zhongheng Zhang ◽  
...  

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.


Author(s):  
Raffi Kamalian ◽  
Alice M. Agogino ◽  
Hideyuki Takagi

In this paper we review the current state of automated MEMS synthesis with a focus on generative methods. We use the design of a MEMS resonator as a case study and explore the role that geometric constraints and human interaction play in a computer-aided MEMS design system based on genetic algorithms.


2018 ◽  
Vol 10 (2) ◽  
pp. 337-346 ◽  
Author(s):  
Mary Kathleen Ladd ◽  
Beth N Peshkin ◽  
Leigha Senter ◽  
Shari Baldinger ◽  
Claudine Isaacs ◽  
...  

Abstract Risk-reducing mastectomy (RRM) and salpingo-oophorectomy (RRSO) are increasingly used to reduce breast and ovarian cancer risk following BRCA1/BRCA2 testing. However, little is known about how genetic counseling influences decisions about these surgeries. Although previous studies have examined intentions prior to counseling, few have examined RRM and RRSO intentions in the critical window between genetic counseling and test result disclosure. Previous research has indicated that intentions at this time point predict subsequent uptake of surgery, suggesting that much decision-making has taken place prior to result disclosure. This period may be a critical time to better understand the drivers of prophylactic surgery intentions. The aim of this study was to examine predictors of RRM and RRSO intentions. We hypothesized that variables from the Health Belief Model would predict intentions, and we also examined the role of affective factors. Participants were 187 women, age 21–75, who received genetic counseling for hereditary breast and ovarian cancer. We utilized multiple logistic regression to identify independent predictors of intentions. 49.2% and 61.3% of participants reported intentions for RRM and RRSO, respectively. Variables associated with RRM intentions include: newly diagnosed with breast cancer (OR = 3.63, 95% CI = 1.20–11.04), perceived breast cancer risk (OR = 1.46, 95% CI = 1.17–1.81), perceived pros (OR = 1.79, 95% CI = 1.38–2.32) and cons of RRM (OR = 0.81, 95% CI = 0.65–0.996), and decision conflict (OR = 0.80, 95% CI = 0.66–0.98). Variables associated with RRSO intentions include: proband status (OR = 0.28, 95% CI = 0.09–0.89), perceived pros (OR = 1.35, 95% CI = 1.11–1.63) and cons of RRSO (OR = 0.72, 95% CI = 0.59–0.89), and ambiguity aversion (OR = 0.79, 95% CI = 0.65–0.95). These data provide support for the role of genetic counseling in fostering informed decisions about risk management, and suggest that the role of uncertainty should be explored further.


Author(s):  
Sorrek Penn-Edwards

The qualitative research methodology of phenomenography has traditionally required a manual sorting and analysis of interview data. In this paper I explore a potential means of streamlining this procedure by considering a computer aided process not previously reported upon. Two methods of lexicological analysis, manual and automatic, were examined from a phenomenographical perspective and compared. It was found that the computer aided process - Leximancer - was a valid investigative tool for use in phenomenography. Using Leximancer was more efficacious than manual operation; the researcher was able to deal with large amounts of data without bias, identify a broader span of syntactic properties, increase reliability, and facilitate reproducibility. The introduction of a computer aided methodology might also encourage other qualitative researchers to engage with phenomenography.


Sign in / Sign up

Export Citation Format

Share Document