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- Karakatsanis, Andreas, et al.
(författare)
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Axillary Staging in the Setting of a Preoperative Diagnosis of Ductal Cancer In Situ (DCIS) : Results of an International Expert Panel and a Critical Guideline Performance Using Frequentist and Bayesian Analysis
- 2020
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Ingår i: Annals of Surgical Oncology. - : Springer. - 1068-9265 .- 1534-4681. ; 27:Suppl. 2, s. S337-S338
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background/Objective: Sentinel lymph node biopsy (SLNB) is not routine in DCIS. Guidelines suggest SLNB when there is high risk for underlying invasion (large size, high grade, symptomatic lesion) or for detection failure (e.g., after mastectomy). However, guidelines and current practice patterns are inconsistent. Moreover, whilst SLNB is thought to be feasible and accurate after wide local excision (WLE), there is less consensus to support its use after oncoplastic breast-conserving surgery (OPBCS), which can reduce the need for mastectomy (Mx) and is gradually adopted as standard of care. The study aim was to assess if guidelines or individualized assessment result in optimal selection of patients for upfront SLNB.Methods: A panel of 28 international experts (20 surgeons, 8 oncologists, Europe 20, USA 5, Asia/Australia 3) was formed, all blind to the identity of the others. They reviewed anonymized patient cases from the SentiNot study (n=184, m. age 60 years, DCIS m. size 4 cm, Grade 2/3= 36%/64%, mass lesions 13,4%, underlying invasion 24.5%) and answer if they would consider upfront SLNB and why. Consensus and majority were set to >75 and >50%. At the same time, 6 independent raters (4 surgeons, 2 oncologists) reviewed guidelines and assessed the same patient cases per each guideline. Accuracy in relation to underlying invasion was assessed by Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) was reported. Agreement was investigated by kappa statistics and decision-making patterns by logistic multivariate regression and cluster analysis. To allow for flexibility and adaptation to current knowledge, both a frequentist and a Bayesian approach were undertaken. Priors were adjusted after a literature review regarding the factors that are commonly thought to be associated with higher risk for underlying invasion.Results: A total of 44,896 decisions were retrieved and analysed. The panel reached consensus/majority for upfront SLNB in 41.3/61.4%, whereas individual rates ranged from 11 to 100%. Agreement among panelists was low (kappa=0.37). In multivariate regression analysis for the entire panel, type of surgery was the most common determinant, (simple WLE=less, OPBCS=more and Mx=constant for SLNB), followed by symptomatic diagnosis and DCIS size. Most (26) members had a clear decision-making pattern regarding SLND, based mainly on DCIS size and type of surgery. Individual decision-making performed modestly in identifying patients with underlying invasion (AUC range 0,47-0,59), resulting mainly in overtreatment in 44-77% of patients. The panel performed similarly by majority (AUC 0,5) and by consensus (AUC 0,55) but “undertreated” 60-75% of patients with invasion, failing to identify them as "high-risk." After the recognition of different decision-making patterns, panelists were divided in subgroups with similar decision-making pattern. Analysis identified subgroups with difference in SLNB rate but not with better AUC. The disagreement among panelists in the same subgroups was significant, not only regarding which patients should undergo SLNB, but also on what factors that recommendation was based on. Eight guidelines with relevant recommendations were identified [USA (ASCO/NCCN), Europe (ESMO), Sweden, Denmark, UK, Netherlands and Italy, retrieval date May 2019]. Agreement among raters for each guideline separately varied (kappa: 0.23-0.9). Interpretation as to whether SLNB should be performed ranged widely (40-90%) and with varying concordance (32-88%). No guideline demonstrated accuracy (AUC range 0.45-0.55). Overtreatment risk was high (50-90%), whereas 10-50% of patients with invasion were not identified as “high- risk.” Agreement across guidelines was low (kappa=0.24), meaning that different patients had similar risk to be treated inaccurately, regardless of which guideline was examined.Conclusions: Individualized decision-making and guideline interpretation may be highly subjective and with low accuracy in terms of prediction of invasive disease, resulting in almost random risk for over- or undertreatment of the axilla in patients with DCIS. This suggests that current views and guidelines should be challenged. More accurate preoperative workup and novel techniques to allow for delayed SLNB may be of value in this setting.
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| 4. |
- Mishra, Nivedita, et al.
(författare)
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Memcached : An Experimental Study of DDoS Attacks for the Wellbeing of IoT Applications
- 2021
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 21:23
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Tidskriftsartikel (refereegranskat)abstract
- Distributed denial‐of‐service (DDoS) attacks are significant threats to the cyber world because of their potential to quickly bring down victims. Memcached vulnerabilities have been targeted by attackers using DDoS amplification attacks. GitHub and Arbor Networks were the victims of Memcached DDoS attacks with 1.3 Tbps and 1.8 Tbps attack strengths, respectively. The bandwidth amplification factor of nearly 50,000 makes Memcached the deadliest DDoS attack vector to date. In recent times, fellow researchers have made specific efforts to analyze and evaluate Memcached vulnerabilities; however, the solutions provided for security are based on best practices by users and service providers. This study is the first attempt at modifying the architecture of Memcached servers in the context of improving security against DDoS attacks. This study discusses the Memcached protocol, the vulnerabilities associated with it, the future challenges for different IoT applications associated with caches, and the solutions for detecting Memcached DDoS attacks. The proposed solution is a novel identification‐pattern mechanism using a threshold scheme for detecting volume‐based DDoS attacks. In the undertaken study, the solution acts as a pre‐emptive measure for detecting DDoS attacks while maintaining low latency and high throughput.
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| 5. |
- Pandya, Sharnil, Researcher, 1984-, et al.
(författare)
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A Study of the Recent Trends of Immunology : Key Challenges, Domains, Applications, Datasets, and Future Directions
- 2021
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 21:23
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Tidskriftsartikel (refereegranskat)abstract
- The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medical Things), genetic intelligence algorithms, smart immunological methodologies, etc., has made this process easier. These technologies can observe relations and patterns that humans do and recognize patterns that are unobservable by humans. Furthermore, these technologies have also enabled us to understand better the different types of cells in the immune system, their structures, their importance, and their impact on our immunity, particularly in the case of debilitating diseases such as cancer. The undertaken study explores the AI methodologies currently in the field of immunology. The initial part of this study explains the integration of AI in healthcare and how it has changed the face of the medical industry. It also details the current applications of AI in the different healthcare domains and the key challenges faced when trying to integrate AI with healthcare, along with the recent developments and contributions in this field by other researchers. The core part of this study is focused on exploring the most common classifications of health diseases, immunology, and its key subdomains. The later part of the study presents a statistical analysis of the contributions in AI in the different domains of immunology and an in‐depth review of the machine learning and deep learning methodologies and algorithms that can and have been applied in the field of immunology. We have also analyzed a list of machine learning and deep learning datasets about the different subdomains of immunology. Finally, in the end, the presented study discusses the future research directions in the field of AI in immunology and provides some possible solutions for the same.
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- Patel, Chirag, et al.
(författare)
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DBGC : Dimension-Based Generic Convolution Block for Object Recognition
- 2022
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 22:5
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Tidskriftsartikel (refereegranskat)abstract
- The object recognition concept is being widely used a result of increasing CCTV surveillance and the need for automatic object or activity detection from images or video. Increases in the use of various sensor networks have also raised the need of lightweight process frameworks. Much research has been carried out in this area, but the research scope is colossal as it deals with open-ended problems such as being able to achieve high accuracy in little time using lightweight process frameworks. Convolution Neural Networks and their variants are widely used in various computer vision activities, but most of the architectures of CNN are application-specific. There is always a need for generic architectures with better performance. This paper introduces the Dimension-Based Generic Convolution Block (DBGC), which can be used with any CNN to make the architecture generic and provide a dimension-wise selection of various height, width, and depth kernels. This single unit which uses the separable convolution concept provides multiple combinations using various dimension-based kernels. This single unit can be used for height-based, width-based, or depth-based dimensions; the same unit can even be used for height and width, width and depth, and depth and height dimensions. It can also be used for combinations involving all three dimensions of height, width, and depth. The main novelty of DBGC lies in the dimension selector block included in the proposed architecture. Proposed unoptimized kernel dimensions reduce FLOPs by around one third and also reduce the accuracy by around one half; semi-optimized kernel dimensions yield almost the same or higher accuracy with half the FLOPs of the original architecture, while optimized kernel dimensions provide 5 to 6% higher accuracy with around a 10 M reduction in FLOPs.
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| 7. |
- Shah, Chirag, et al.
(författare)
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Collaborative information seeking : Consolidating the past, creating the future
- 2013
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Ingår i: Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. - New York, NY, USA : ACM. - 9781450313322 ; , s. 321-325
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Konferensbidrag (refereegranskat)abstract
- The notion that information seeking is not always a solitary activity, and that people working in collaboration for information intensive tasks should be studied and supported, has become more prevalent in the recent years than ever before. The field of collaborative information seeking (CIS) is re-emerging, and bringing many researchers and practitioners from various disciplines. This workshop is an effort to gather a small and motivated set of such participants. The workshop will incorporate discussions on theoretical foundations of CIS as well as its applications. It will bring together researchers from both academia and industry, working in the fields of CSCW, CSCL, IR, HCI, and PIM to share their ideas, questions, and opinions on how theories and practices from different domains can be brought together to create a strong and rich path ahead for collaborative information seeking/retrieval/searching as well as collective information synthesis and sense-making.
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| 8. |
- Shah, Chirag, et al.
(författare)
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Collaborative Information Seeking [Guest editors' introduction]
- 2014
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Ingår i: Computer. - 0018-9162 .- 1558-0814. ; 47:3, s. 22-25
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- People often engage in collaborative information seeking to achieve common goals, enlist expertise, increase the scope of what can be searched, and even simply to help others. In today's era of increased user-generated content and online sharing, computer and information scientists have a renewed interest in collaborative information seeking as an exciting area of research and development, with applications that range from education to e-commerce, with implications for areas that range from libraries to legal informatics. The Web extra at http://youtu.be/CXnNut7hKsU is a video in which proponents of collaborative information seeking discuss why supporting people's innate behavior and the need for working together while seeking and using information are important to computer science. Featured speakers include Chirag Shah, Rob Capra, Madhu Reddy, Meredith Ringel Morris, Roberto González-Ibáñez, and Michael B. Twidale.
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| 9. |
- Shah, Chirag, et al.
(författare)
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Research agenda for social and collaborative information seeking
- 2017
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Ingår i: Library & Information Science Research. - : Elsevier BV. - 0740-8188 .- 1873-1848. ; 39:2, s. 140-146
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Forskningsöversikt (refereegranskat)abstract
- Scholars in diverse fields of inquiry have identified the need to expand individual-based information seeking and behavior models and systems to incorporate social as well as collaborative dimensions. However, the research areas of Social Information Seeking (SIS) and Collaborative Information Seeking (CIS) have been largely disconnected from one another despite a few notable attempts to study them under one umbrella. Researchers in these communities have recently realized the value of bringing SIS and CIS together for two main reasons: often it is impossible to separate social and collaborative dimensions in a project; and by considering these two aspects of information seeking, we may be able to support human information behavior in ways not previously possible. A brief synthesis of work in the domains of SIS and CIS is presented here. Then, an integrated view is presented to consider Social and Collaborative Information Seeking (SCIS) as an intersection and extension of SIS and CIS. Benefits of this approach are discussed and the integrated view is used as the basis to present a research agenda that outlines opportunities and challenges unique to SCIS.
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| 10. |
- Shah, Chirag, et al.
(författare)
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Workshop on Social and Collaborative Information Seeking (SCIS)
- 2015
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Ingår i: SIGIR Forum. - : Association for Computing Machinery (ACM). - 0163-5840 .- 1558-0229. ; 49:2, s. 117-122
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Tidskriftsartikel (refereegranskat)abstract
- This is a report from the Workshop on Social and Collaborative Information Seeking (SCIS), held on May 14-15, 2015 at Rutgers University. Twenty-eight participants contributed to the workshop in the form of short talks and work sessions. Outcomes from the workshop include a "research roadmap" of important future research needed in the area of social and collaborative search. The report presented here summarizes the short talks and the discussions that took place in six breakout groups. The report ends with pointers for future directions (research roadmap) and a few take-away points.
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