| 1. |
- Nesti, Cedric, et al.
(författare)
-
Hemicolectomy versus appendectomy for patients with appendiceal neuroendocrine tumours 1-2 cm in size : a retrospective, Europe-wide, pooled cohort study
- 2023
-
Ingår i: The Lancet Oncology. - : Elsevier. - 1470-2045 .- 1474-5488. ; 24:2, s. 187-194
-
Tidskriftsartikel (refereegranskat)abstract
- BackgroundAwareness of the potential global overtreatment of patients with appendiceal neuroendocrine tumours (NETs) of 1–2 cm in size by performing oncological resections is increasing, but the rarity of this tumour has impeded clear recommendations to date. We aimed to assess the malignant potential of appendiceal NETs of 1–2 cm in size in patients with or without right-sided hemicolectomy.MethodsIn this retrospective cohort study, we pooled data from 40 hospitals in 15 European countries for patients of any age and Eastern Cooperative Oncology Group performance status with a histopathologically confirmed appendiceal NET of 1–2 cm in size who had a complete resection of the primary tumour between Jan 1, 2000, and Dec 31, 2010. Patients either had an appendectomy only or an appendectomy with oncological right-sided hemicolectomy or ileocecal resection. Predefined primary outcomes were the frequency of distant metastases and tumour-related mortality. Secondary outcomes included the frequency of regional lymph node metastases, the association between regional lymph node metastases and histopathological risk factors, and overall survival with or without right-sided hemicolectomy. Cox proportional hazards regression was used to estimate the relative all-cause mortality hazard associated with right-sided hemicolectomy compared with appendectomy alone. This study is registered with ClinicalTrials.gov, NCT03852693.Findings282 patients with suspected appendiceal tumours were identified, of whom 278 with an appendiceal NET of 1–2 cm in size were included. 163 (59%) had an appendectomy and 115 (41%) had a right-sided hemicolectomy, 110 (40%) were men, 168 (60%) were women, and mean age at initial surgery was 36·0 years (SD 18·2). Median follow-up was 13·0 years (IQR 11·0–15·6). After centralised histopathological review, appendiceal NETs were classified as a possible or probable primary tumour in two (1%) of 278 patients with distant peritoneal metastases and in two (1%) 278 patients with distant metastases in the liver. All metastases were diagnosed synchronously with no tumour-related deaths during follow-up. Regional lymph node metastases were found in 22 (20%) of 112 patients with right-sided hemicolectomy with available data. On the basis of histopathological risk factors, we estimated that 12·8% (95% CI 6·5 –21·1) of patients undergoing appendectomy probably had residual regional lymph node metastases. Overall survival was similar between patients with appendectomy and right-sided hemicolectomy (adjusted hazard ratio 0·88 [95% CI 0·36–2·17]; p=0·71).InterpretationThis study provides evidence that right-sided hemicolectomy is not indicated after complete resection of an appendiceal NET of 1–2 cm in size by appendectomy, that regional lymph node metastases of appendiceal NETs are clinically irrelevant, and that an additional postoperative exclusion of metastases and histopathological evaluation of risk factors is not supported by the presented results. These findings should inform consensus best practice guidelines for this patient cohort.
|
|
| 2. |
- Cukurova, Mutlu, et al.
(författare)
-
Modelling Collaborative Problem-solving Competence with Transparent Learning Analytics : Is Video Data Enough?
- 2020
-
Ingår i: LAK20. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 270-275
-
Konferensbidrag (refereegranskat)abstract
- In this study, we describe the results of our research to model collaborative problem-solving (CPS) competence based on analytics generated from video data. We have collected similar to 500 mins video data from 15 groups of 3 students working to solve design problems collaboratively. Initially, with the help of OpenPose, we automatically generated frequency metrics such as the number of the face-in-the-screen; and distance metrics such as the distance between bodies. Based on these metrics, we built decision trees to predict students' listening, watching, making, and speaking behaviours as well as predicting the students' CPS competence. Our results provide useful decision rules mined from analytics of video data which can be used to inform teacher dashboards. Although, the accuracy and recall values of the models built are inferior to previous machine learning work that utilizes multimodal data, the transparent nature of the decision trees provides opportunities for explainable analytics for teachers and learners. This can lead to more agency of teachers and learners, therefore can lead to easier adoption. We conclude the paper with a discussion on the value and limitations of our approach.
|
|
| 3. |
- Ruffaldi, Emanuele, et al.
(författare)
-
Data collection and processing for a multimodal learning analytic system
- 2016
-
Ingår i: Proceedings of 2016 SAI Computing Conference (SAI). - : IEEE. - 9781467384605 - 9781467384612 ; , s. 858-863
-
Konferensbidrag (refereegranskat)abstract
- Learning Analytic (LA) systems are aimed at supporting teachers in understanding the learning process by analyzing the information and the interaction of students with computer systems. In the case of a project-based learning process there is a need of introducing measure the student’ activity as acquired via multiple modalities and then processed. The acquisition and processing needs to take into account the specificities of the learning context and deployment at schools, in particular in terms of system architecture. The paper proposes an architecture for the acquisition and processing of data for project-based LA designed to be interoperable and scalable. System design, details of the solutions and brief examples of acquired data are presented.
|
|
| 4. |
- Spikol, Daniel, et al.
(författare)
-
Estimation of Success in Collaborative Learning Based on Multimodal Learning Analytics Features
- 2017
-
Ingår i: Proceedings 17th International Conference on Advanced Learning Technologies - ICALT 2017. - : IEEE. ; , s. 269-273
-
Konferensbidrag (refereegranskat)abstract
- Abstract: Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates high-fidelity synchronised multimodal recordings of small groups of learners interacting from diverse sensors that include computer vision, user generated content, and data from the learning objects (like physical computing components or laboratory equipment). We processed and extracted different aspects of the students' interactions to answer the following question: which features of student group work are good predictors of team success in open-ended tasks with physical computing? The answer to the question provides ways to automatically identify the students' performance during the learning activities.
|
|
