scholarly journals Analyzing and predicting spear-phishing using machine learning methods

2020 ◽  
Vol 10 (4) ◽  
pp. 262-273
Author(s):  
Samad Dadvandipour ◽  
Aadil Gani Ganie
Keyword(s):  
False Positive ◽  
Credit Card ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
False Negative ◽  
Svm Classifier ◽  
Critical Material ◽  
Coherence Score ◽  
Percent Accuracy ◽  
The Impact

Phishing implies misdirecting the client by masking himself/herself as a reliable individual, to take the Critical material, for example, bank account number, credit card numbers, and so on; one of the noticeably utilized Phishing these days is spear phishing, and it is one of the effective phishing assaults given its social, mental boundaries. In this paper, we will mitigate the impact of spear phishing by utilizing the multi-layer approach. The multi-layer approach is the best method of managing the web interruption, as the intruder needs to experience shift levels. Practically all the scientists are dealing with the content of the email; however, this paper picks a novel method to counter the phishing messages by utilizing both the attachment and content of an email. We applied sentimental analysis on emails, including both content of the email and the attachment, to check whether they are spam or not using SVM classifier and Randomforest Classifier; the former showed 96 percent accuracy while, as later offers 97.66 percent accuracy. SVM showed false-positive 0 percent and false-negative 4 percent, while RandomForest showed 0 percent false-positive and 2.33 percent false-negative ratios. We also performed topic modeling using LDA(Latent Dirichlet Allocation)) from Gensim package to get the dominant topics in our dataset. We visualized the results of our topic model using pyLDvis. The perplexity and coherence score of our topic model is -12.897670565510511 and 0.44700287476452394, respectively.

Multivariate interpretation of laboratory tests used in monitoring patients

1990 ◽  
Vol 36 (5) ◽  
pp. 748-751 ◽  
Author(s):  
H B Slotnick ◽  
P Etzell
Keyword(s):  
Small Groups ◽  
False Positive ◽  
Laboratory Tests ◽  
False Negative ◽  
Test Results ◽  
Laboratory Findings ◽  
Bonferroni Inequality ◽  
The Impact

Abstract This study demonstrates an approach to the problem of minimizing false-negative and false-positive laboratory findings. In this approach, we consider the fact that results of laboratory tests are correlated, utilize within-person test results to interpret current results, and minimize the impact of multivariate conservatism by examining test results in small groups. The procedure requires panels of tests to be divided into related subpanels, testing each subpanel independently, and using the Bonferroni inequality to determine whether any of the observed values for a given subpanel is "out-of-range." The procedure is demonstrated, and its limitations are observed and discussed.

scholarly journals Factors associated with false negative and false positive results of prostate-specific antigen (PSA) and the impact on patient health

Medicine ◽  
2019 ◽  
Vol 98 (40) ◽  
pp. e17451 ◽  
Author(s):  
Mari Carmen Bernal-Soriano ◽  
Lucy A. Parker ◽  
Maite López-Garrigos ◽  
Ildefonso Hernández-Aguado ◽  
Juan P. Caballero-Romeu ◽  
...  
Keyword(s):  
Prostate Specific Antigen ◽  
False Positive ◽  
False Negative ◽  
Specific Antigen ◽  
Factors Associated ◽  
Patient Health ◽  
The Impact ◽  
Positive Results

scholarly journals Can Twitter messaging help corporations mitigate the impact of ethical scandals? We topic-model pre-scandal tweets of 92 ‘offenders’ to investigate

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shivani Raheja ◽  
Max Chipulu
Keyword(s):  
Web Application ◽  
Latent Dirichlet Allocation ◽  
Corporate Strategy ◽  
Topic Model ◽  
New York Times ◽  
Customer Relationship ◽  
Content Type ◽  
Global Issues ◽  
The Impact ◽  
Twitter Messaging

Purpose This paper aims to examine whether Twitter messaging can help mitigate the harm corporations suffer in the aftermath of ethical scandals. Design/methodology/approach This paper applies Web Application Programming Interfaces (API) on the Guardian and New York Times news archives to find corporations that suffered scandals between 2014 and 2019, revealing 92 publicly listed companies in the UK. Using Twitter API and the Python library, Getoldtweets, this paper extracts historical, pre-scandal – i.e. pre-2014 – tweets of the 92 firms. The paper topic-models the tweets data using Latent Dirichlet Allocation (LDA). This paper then subjects the topics to multidimensional scaling (MDS) to examine commonalities among them. Findings LDA reveals 10 topics, which group under 5 themes; these are product marketing, urgent signalling of “greenness”, customer relationship management, corporate strategy and news feeds. MDS suggests that the topics further congregate into two meta-themes of future-oriented versus immediate and individual versus global. Practical implications Provided they are sincere and legitimate, corporations’ tweets on global issues with a green agenda should help cushion the impact of ethical scandals. Overall, however, the findings suggest that Twitter messaging could be a double-edged sword, and underscore the importance of strategy. Originality/value The paper offers a first exploration of the relevance of corporate Twitter messaging in mitigating ethical scandals.

scholarly journals Determining the impact of psychosis on rates of false-positive and false-negative diagnosis in Alzheimer's disease

2017 ◽  
Vol 3 (3) ◽  
pp. 385-392 ◽  
Author(s):  
Corinne E. Fischer ◽  
Winnie Qian ◽  
Tom A. Schweizer ◽  
Zahinoor Ismail ◽  
Eric E. Smith ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
False Positive ◽  
False Negative ◽  
The Impact

scholarly journals SP3.2.9 The concordance between emergency CT reporting in non-traumatic abdominal pain with surgical findings at laparotomy

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Claire Edwin ◽  
Alice Bradley ◽  
Filomena Liccardo ◽  
Georgina Bowman ◽  
Sophie Crisford ◽  
...  
Keyword(s):  
False Positive ◽  
False Negative ◽  
Ct Imaging ◽  
Patient Treatment ◽  
Emergency Laparotomy ◽  
Abdominal Ct ◽  
Out Of Hours ◽  
Clinical Episode ◽  
The Impact ◽  
Audit Standards

Abstract Aims Abdominal CT imaging is commonly used to assess the acute abdomen, and is relied upon by clinicians in decision making, often influencing the timeliness of intervention. Increased demand for CT imaging has led to departments out-sourcing reporting out of hours. The aim of this audit was to evaluate the concordance between emergency laparotomy findings and pre-operative CT reports. Methods 115 patients underwent emergency laparotomy with a pre-operative CT scan pertinent to the clinical episode (May 2019-October 2020). 2 surgical assessors independently assessed the CT reports and laparotomy findings to determine discrepancies. Using published audit standards, discrepancies were defined as major-felt to affect patient treatment- and further classified as false positive, false negative, misdiagnosis, indeterminate; or minor and unlikely to change course of patient care. Results 32/115 had discrepancies, 28/32 major (16/28 misdiagnosis, 4/28 false negative, 3/28 false positive, and 5/28 indeterminate). 71/115 reported by in house radiology. 19/71 discrepancies reported in house (16 major, 3 minor), 13/32 discrepancies reported by out of hours service (12 major, 1 minor). Relative risk of major discrepancies between in house radiology and out of hours service was 1.2 (p = 0.5). Conclusions Published audit standards are that CT reports should have >90% concordance with laparotomy findings; this audit found concordance in 76%. Further analysis comparing gastrointestinal vs. non-gastrointestinal specialist radiologist to assess the impact on concordance will be performed. We aim to explore the discrepancies, and seek to identify if our imaging and operating practices can be improved.

Selective Use of Intraoperative Touch Prep Analysis of Sentinel Nodes in Breast Cancer

2005 ◽  
Vol 71 (11) ◽  
pp. 955-962 ◽  
Author(s):  
Rachel C. Forbes ◽  
Clovis Pitchford ◽  
Jean F. Simpson ◽  
Glen C. Balch ◽  
Mark C. Kelley
Keyword(s):  
Breast Cancer ◽  
Predictive Value ◽  
False Positive ◽  
False Negative ◽  
Nodal Metastasis ◽  
Axillary Lymph ◽  
Sentinel Nodes ◽  
Number Of Patients ◽  
The Impact ◽  
Positive Results

Imprint cytology (touch prep) is often used for intraoperative examination of sentinel nodes in breast cancer. This allows axillary lymph node dissection (ALND) to be performed immediately for tumor-positive nodes. We evaluated the accuracy of touch prep examination of sentinel nodes and its role in the surgical treatment of breast cancer. We analyzed 169 breast cancer patients who underwent 170 lymphatic mapping procedures with intraoperative touch prep examination. Results from the touch prep were correlated with histopathology and clinical variables. There were 115 true-negative, 35 true-positive, 15 false-negative, and 5 false-positive results. Touch prep had a sensitivity of 70 per cent and specificity of 96 per cent. Positive predictive value, negative predictive value, and diagnostic accuracy were all 88 per cent. The false-negative rate was 30 per cent and correlated with the size of the nodal metastasis and number of involved nodes, but not other patient factors. Touch prep is useful for the evaluation of sentinel nodes in breast cancer, but it has a lower sensitivity than initially reported, particularly in patients with micrometastases. False positive results occur, although they may be reduced after experience with the technique. We recommend that suspicious findings on touch prep should be confirmed by frozen section and that ALND only be performed for histologically documented metastases. We currently perform touch prep only in patients who are at high risk of nodal metastasis or will undergo mastectomy. This improves operative efficiency and limits the impact of false positive and negative results without dramatically increasing the number of patients who require a second surgical procedure.

scholarly journals Content analysis of tweets for a better understanding of the context around the individual’s low back pain experience (Preprint)

2020 ◽  
Author(s):  
Robert Robert ◽  
Pari Delir Haghighi ◽  
Frada Burstein ◽  
Donna Urquhart ◽  
Flavia Cicuttini
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Low Back Pain ◽  
Back Pain ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Qualitative Studies ◽  
Low Back ◽  
Contextual Variables ◽  
Coherence Score

BACKGROUND Although personal experiences of low back pain have traditionally been explored through qualitative studies, social media content analysis has the potential to be used to complement these studies by providing deeper understanding of how problems such as pain are perceived by those how have it, and the effect of the contextual variables on individuals and the community. OBJECTIVE The objective of this study was to perform content analysis of tweets for identifying contextual variables of the low back pain (LBP) experience from a first-person perspective to better understand individuals’ beliefs and perceptions. METHODS We analysed 896,867 cleaned tweets about low back pain between 1 January 2014 – 31 December 2018. We tested and compared Latent Dirichlet Allocation (LDA), Dirichlet Multinomial Mixture (DMM), GPU-DMM, Biterm Topic Model (BTM) and Non-negative Matrix factorization (NMF) for identifying topics associated with tweets. A coherence score was determined to identify the best model. RESULTS LDA outperformed all other algorithms resulting in the highest coherence score. The best model was LDA with 60 topics with coherence score 0.562. With input from domain experts, the 60 topics were validated and grouped into 19 contextual categories. “Emotion and Beliefs” had the largest proportion of the total tweets (17.6%), followed by “Physical Activity” (13.85%) and “Daily Life” (9%), while “Food and Drink”, “Weather” and “Not Being Understood” had the least (1.29%, 1.13% and 1.02% respectively). Of the 11 topics within “emotions and beliefs”, 72% had negative sentiment. CONCLUSIONS Using social media allows access to the data from a larger, heterogonous and geographically distributed population which is not possible using traditional qualitative methods that are generally limited to a small population. Individuals may be more inclined to express their feelings and emotions freely on social media sites, where the data is collected in an unsolicited manner, compared to common, rigid data collection methods. A content analysis of tweets identified common themes in the area of low back pain that are consistent with findings from conventional qualitative studies but provide a more granular view of the individuals’ perspectives related to low back pain. This understanding has the potential to assist with developing more effective and personalized models of care to improve treatment outcomes.

The lifetime economic burden of inaccurate HER2 testing: Comparing false positive and false negative HER2+ early breast cancer patients in the United States.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6626-6626
Author(s):  
Louis Garrison ◽  
Joseph Babigumira ◽  
Anthony Masaquel ◽  
Bruce Wang ◽  
Deepa Lalla ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Breast Cancer ◽  
Economic Burden ◽  
False Positive ◽  
False Negative ◽  
The United States ◽  
Test Accuracy ◽  
Her2 Testing ◽  
Life Years ◽  
The Impact

6626 Background: Trastuzumab is administered to patients with early breast cancer (EBC) whose tumors test positive for HER2 using IHC or FISH diagnostic tests. However, due to test characteristics and testing heterogeneity, patients may be misdiagnosed as false positive (FP) or false negative (FN). This analysis estimates the lifetime economic burden of inaccurate HER2 testing in the US. Methods: We developed a national-level economic model to estimate the impact on healthcare costs and quality-adjusted life years (QALYs) in both groups in 2012. The model estimates the expected number of FP and FN patients using literature-derived estimates of each test’s sensitivity, specificity, and utilization. Based on estimates from the literature, a FP patient would generate unneeded trastuzumab costs of about $56,000 and experience a chance (2.9%) of related cardiotoxicity; an FN patient would save $56,000 in trastuzumab costs, but lose 1.7 QALYs of life expectancy and face a greater likelihood of recurrence and associated costs ($42,000) to treat metastatic disease. A net monetary benefit approach (valuing healthy life years at $100,000) is used to compare the lifetime economic burden for FP and FN. Results: The estimated overall proportions of FP and FN are 2.8% and 2.2% of 227,000 EBC patients, resulting in about 6,400 and 5,000 women in each group, respectively. Overall, approximately 8600 QALYs would be lost among FN patients who do not receive trastuzumab. We estimate the incremental per-patient lifetime burden of an FP to be about $57,000, and for an FN to be about $118,000. The implied incremental loss to society for FPs is $362 million and for FNs is $596 million. Conclusions: Current testing practices and treatment patterns for HER2+ EBC patients result in misdiagnosis and non-optimal treatment in approximately 11,500 patients each year: the combined total economic loss to society is nearly $1 billion. The greater share of the loss is among FN patients who would have benefited from trastuzumab, but did not receive it. The significant annual burden of HER2 misdiagnosis suggests that substantial societal investments to improve HER2 test accuracy should be considered.

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