scholarly journals Transfer Detection of YOLO to Focus CNN’s Attention on Nude Regions for Adult Content Detection

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 26
Author(s):  
Nouar AlDahoul ◽  
Hezerul Abdul Karim ◽  
Mohd Haris Lye Abdullah ◽  
Mohammad Faizal Ahmad Fauzi ◽  
Abdulaziz Saleh Ba Wazir ◽  
...  
Keyword(s):  
Recent Literature ◽  
False Negative ◽  
False Negative Rate ◽  
Regions Of Interest ◽  
Support Vector ◽  
Small Scale ◽  
High False Negative Rate ◽  
Diverse Backgrounds ◽  
Ablation Study ◽  
The Impact

Video pornography and nudity detection aim to detect and classify people in videos into nude or normal for censorship purposes. Recent literature has demonstrated pornography detection utilising the convolutional neural network (CNN) to extract features directly from the whole frames and support vector machine (SVM) to classify the extracted features into two categories. However, existing methods were not able to detect the small-scale content of pornography and nudity in frames with diverse backgrounds. This limitation has led to a high false-negative rate (FNR) and misclassification of nude frames as normal ones. In order to address this matter, this paper explores the limitation of the existing convolutional-only approaches focusing the visual attention of CNN on the expected nude regions inside the frames to reduce the FNR. The You Only Look Once (YOLO) object detector was transferred to the pornography and nudity detection application to detect persons as regions of interest (ROIs), which were applied to CNN and SVM for nude/normal classification. Several experiments were conducted to compare the performance of various CNNs and classifiers using our proposed dataset. It was found that ResNet101 with random forest outperformed other models concerning the F1-score of 90.03% and accuracy of 87.75%. Furthermore, an ablation study was performed to demonstrate the impact of adding the YOLO before the CNN. YOLO–CNN was shown to outperform CNN-only in terms of accuracy, which was increased from 85.5% to 89.5%. Additionally, a new benchmark dataset with challenging content, including various human sizes and backgrounds, was proposed.

scholarly journals High mortality with High false negative rate: COVID-19 infection in patients with hematologic malignancies

2021 ◽  
Vol 106 ◽  
pp. 106582
Author(s):  
Alex Niu ◽  
Bo Ning ◽  
Francisco Socola ◽  
Hana Safah ◽  
Tim Reynolds ◽  
...  
Keyword(s):  
High Mortality ◽  
False Negative ◽  
False Negative Rate ◽  
Hematologic Malignancies ◽  
Negative Rate ◽  
High False Negative Rate

Abstract 1122‐000034: Systematic CT‐Perfusion acquisition in All Suspected Stroke Patients Increases Vascular Occlusion Detection and Thrombectomy Rates

2021 ◽  
Vol 1 (S1) ◽  
Author(s):  
Marta Olive‐Gadea ◽  
Manuel Requena ◽  
Facundo Diaz ◽  
Alvaro Garcia‐Tornel ◽  
Marta Rubiera ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Clinical Symptoms ◽  
Ct Perfusion ◽  
False Negative ◽  
False Negative Rate ◽  
Vascular Occlusion ◽  
Stroke Patients ◽  
Imaging Protocols ◽  
The Impact

Introduction : In acute ischemic stroke patients, current guidelines recommend noninvasive vascular imaging to identify intracranial vessel occlusions (VO) that may benefit from endovascular treatment (EVT). However, VO can be missed in CT angiography (CTA) readings. We aim to evaluate the impact of consistently including CT perfusion (CTP) in admission stroke imaging protocols on VO diagnosis and EVT rates. Methods : We included patients with a suspected acute ischemic stroke that underwent urgent non‐contrast CT, CTA and CTP from April to October 2020. Hypoperfusion areas defined by Tmax>6s delay (RAPID software), congruent with the clinical symptoms and a vascular territory, were considered due to a VO (CTP‐VO). Cases in which mechanical thrombectomy was performed were defined as therapeutically relevant VO (EVT‐VO). For patients that received EVT, site of VO according to digital subtraction angiography was recorded. Two experienced neuroradiologists blinded to CTP but not to clinical symptoms, retrospectively evaluated NCCT and CTA to identify intracranial VO (CTA‐VO). We analyzed CTA‐VO sensitivity and specificity at detecting CTP‐VO and EVT‐VO respecitvely. We performed a logistic regression to test the association of Tmax>6s volumes with CTA‐VO identification and indication of EVT. Results : Of the 338 patients included in the analysis, 157 (46.5%) presented a CTP‐VO, (median Tmax>6s: 73 [29‐127] ml). CTA‐VO was identified in 83 (24.5%) of the cases. Overall CTA‐VO sensitivity for the detection of CTP‐VO was 50.3% and specificity was 97.8%. Higher hypoperfusion volume was associated with an increased CTA‐VO detection, with an odds ratio of 1.03 (95% confidence interval 1.02‐1.04) (figure). DSA was indicated in 107 patients; in 4 of them no EVT was attempted due to recanalization or a too distal VO in the first angiographic run. EVT was performed in 103 patients (30.5%. Tmax>6s: 102 [63‐160] ml), representing 65.6% of all CTP‐VO. Overall CTA‐VO sensitivity for the detection of EVT‐VO was 69.9%. The CTA‐VO sensitivity for detecting patients with indication of EVT according to clinical guidelines was as follows: 91.7% for ICA occlusions and 84.4% for M1‐MCA occlusions. For all other occlusion sites that received EVT, the CTA‐VO sensitivity was 36.1%. The overall specificity was 95.3%. Among patients who received EVT, CTA‐VO was not detected in 31 cases, resulting in a false negative rate of 30.1%. False negative CTA‐VO cases had lower Tmax>6s volumes (69[46‐99.5] vs 126[84‐169.5]ml, p<0.001) and lower NIHSS (13[8.5‐16] vs 17[14‐21], p<0.001). Conclusions : Systematically including CTP perfusion in the acute stroke admission imaging protocols may increase the diagnosis of VO and rate of EVT.

scholarly journals False Negative Mitigation in Group Testing for COVID-19 Screening

2021 ◽  
Vol 8 ◽  
Author(s):  
Amir Reza Alizad Rahvar ◽  
Safar Vafadar ◽  
Mehdi Totonchi ◽  
Mehdi Sadeghi
Keyword(s):  
Viral Load ◽  
False Negative ◽  
Group Testing ◽  
False Negative Rate ◽  
Screening Strategy ◽  
Web Interface ◽  
Rt Pcr ◽  
Promising Candidate ◽  
Testing Method ◽  
High False Negative Rate

After lifting the COVID-19 lockdown restrictions and opening businesses, screening is essential to prevent the spread of the virus. Group testing could be a promising candidate for screening to save time and resources. However, due to the high false-negative rate (FNR) of the RT-PCR diagnostic test, we should be cautious about using group testing because a group's false-negative result identifies all the individuals in a group as uninfected. Repeating the test is the best solution to reduce the FNR, and repeats should be integrated with the group-testing method to increase the sensitivity of the test. The simplest way is to replicate the test twice for each group (the 2Rgt method). In this paper, we present a new method for group testing (the groupMix method), which integrates two repeats in the test. Then we introduce the 2-stage sequential version of both the groupMix and the 2Rgt methods. We compare these methods analytically regarding the sensitivity and the average number of tests. The tradeoff between the sensitivity and the average number of tests should be considered when choosing the best method for the screening strategy. We applied the groupMix method to screening 263 people and identified 2 infected individuals by performing 98 tests. This method achieved a 63% saving in the number of tests compared to individual testing. Our experimental results show that in COVID-19 screening, the viral load can be low, and the group size should not be more than 6; otherwise, the FNR increases significantly. A web interface of the groupMix method is publicly available for laboratories to implement this method.

Pathologic Assessment of Computerized Tomography Accuracy for the Evaluation of the Laryngeal Cartilaginous Frame Work in Laryngopharyngeal Carcinomas

1989 ◽  
Vol 75 (2) ◽  
pp. 156-162 ◽  
Author(s):  
Sandro Sulfaro ◽  
Francesco Querin ◽  
Luigi Barzan ◽  
Mario Lutman ◽  
Roberto Comoretto ◽  
...  
Keyword(s):  
Computerized Tomography ◽  
False Positive ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Cartilage Destruction ◽  
High False Negative Rate ◽  
Positive Rate ◽  
Pathologic Assessment ◽  
Low Sensitivity

Sixty-six whole-organ sectioned laryngopharyngectomy specimens removed for cancer during a seven-year period were uniformly examined to determine the accuracy of preoperative high resolution computerized tomography (CT) for detection of cartilaginous involvement. Our results indicate that CT has a high overall specificity (88.2%) but a low sensitivity (47.1 %); we observed a high false-negative rate (26.5%) and a fairly low false-positive rate (5.9%). Massive cartilage destruction was easily assessed by CT, whereas both small macroscopic and microscopic neoplastic foci of cartilaginous invasion were missed on CT scans. Moreover, false-positive cases were mainly due to proximity of the tumor to the cartilage. Clinical implications of these results are discussed.

scholarly journals 0587 Convenience vs Accuracy: Negative Predictability of the Home Sleep Test in Clinical Practice

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A225-A225
Author(s):  
C D Morse ◽  
S Meissner ◽  
L Kodali
Keyword(s):  
Clinical Practice ◽  
Sleep Apnea ◽  
False Negative ◽  
False Negative Rate ◽  
True Negative ◽  
Negative Rate ◽  
High False Negative Rate ◽  
Obstructive Sleep ◽  
Respiratory Disturbance ◽  
Lost To Follow Up

Abstract Introduction Sleep apnea is a serious disorder associated with numerous health conditions. In clinical practice, providers order screening home sleep testing (HST) for obstructive sleep apnea (OSA); however, there is limited research about the negative predictive value (NPV) and false negative rate of this test. Providers may not understand HST limitations; therefore, what is the NPV and false negative rate in clinical practice? Methods A retrospective study of non-diagnostic HST is conducted in a Northeastern US rural community sleep clinic. The study population includes adult patients ≥ 18 years old who underwent HST from 2016-2019. The non-diagnostic HST result is compared to the gold standard, the patient’s nocturnal polysomnogram (NPSG). The results provide the NPV (true negative/total) and false negative (true positive/total) for the non-diagnostic HST. Results We identified 211 potential patients with a mean age of 43 years, of which 67% were female. Of those, 85% (n=179) underwent NPSG, with the others declining/delaying testing or lost to follow up. The non-diagnostic HST showed 15.6% NPV for no apnea using AHI&lt;5 and 8.4% NPV using respiratory disturbance index (tRDI)&lt;5. The false negative rate for AHI/tRDI was 84.4% and 91.6%, respectively. The AHI for positive tests ranged from 5-89 per hour (mean AHI 14.9/tRDI 16/hour), of which OSA was identified with an elevated AHI (≥5) ranging from 54.2% mild, 21.8% moderate, and 8.4% severe. Conclusion The high false negative rate of the HST is alarming. Some providers and patients may forgo NPSG after non-diagnostic HST due to a lack of understanding for the HST’s limitations. Knowing that the non-diagnostic HST is a very poor predictor of no sleep apnea will help providers advise patients appropriately for the necessity of the NPSG. The subsequent NPSG provides an accurate diagnosis and, therefore, an informed decision about pursuing or eschewing sleep apnea treatment. Support none

scholarly journals A Deep-Learning-Based Framework for Automated Diagnosis of COVID-19 Using X-ray Images

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 419 ◽  
Author(s):  
Irfan Ullah Khan ◽  
Nida Aslam
Keyword(s):  
Deep Learning ◽  
False Negative ◽  
False Negative Rate ◽  
Complex Nature ◽  
Learning Models ◽  
Daily Lives ◽  
X Ray ◽  
High False Negative Rate ◽  
Diagnosis Method ◽  
Novel Coronavirus

The emergence and outbreak of the novel coronavirus (COVID-19) had a devasting effect on global health, the economy, and individuals’ daily lives. Timely diagnosis of COVID-19 is a crucial task, as it reduces the risk of pandemic spread, and early treatment will save patients’ life. Due to the time-consuming, complex nature, and high false-negative rate of the gold-standard RT-PCR test used for the diagnosis of COVID-19, the need for an additional diagnosis method has increased. Studies have proved the significance of X-ray images for the diagnosis of COVID-19. The dissemination of deep-learning techniques on X-ray images can automate the diagnosis process and serve as an assistive tool for radiologists. In this study, we used four deep-learning models—DenseNet121, ResNet50, VGG16, and VGG19—using the transfer-learning concept for the diagnosis of X-ray images as COVID-19 or normal. In the proposed study, VGG16 and VGG19 outperformed the other two deep-learning models. The study achieved an overall classification accuracy of 99.3%.

scholarly journals Septic arthritis of the knee: the use and effect of antibiotics prior to diagnostic aspiration

2012 ◽  
Vol 94 (5) ◽  
pp. 351-355 ◽  
Author(s):  
P Hindle ◽  
E Davidson ◽  
LC Biant
Keyword(s):  
Septic Arthritis ◽  
Joint Infection ◽  
False Negative ◽  
False Negative Rate ◽  
Standard Test ◽  
Entire Cohort ◽  
High False Negative Rate ◽  
Total Knee ◽  
Prosthetic Knees ◽  
No Gold Standard

Septic arthritis of the native knee joint and total knee arthroplasty both cause diagnostic and treatment issues. There is no gold standard test to diagnose a joint infection and the use of joint aspiration is commonly relied on. It is widely accepted by orthopaedic surgeons that antibiotics should be withheld until aspiration has been performed to increase the odds of identifying an organism. Patients often present to other specialties that may not be as familiar with these principles. Our study found that 25 (51%) of the 49 patients treated for septic arthritis of the native or prosthetic knee in our unit over a 3-year period had received antibiotics prior to discussion or review by the on-call orthopaedic service. Patients were significantly less likely to demonstrate an organism on initial microscopy (entire cohort: p=0.001, native knees: p=0.006, prosthetic knees: p=0.033) or on subsequent culture (entire cohort: p=0.001, native knees: p=0.017, prosthetic knees: p=0.012) of their aspirate if they had received antibiotics. The sensitivity of microscopy in all patients dropped from 58% to 12% when patients had received antibiotics (native knees: 46% to 0%, prosthetic knees: 72% to 27%). The sensitivity of the culture dropped from 79% to 28% in all patients when the patient had received antibiotics (native knees: 69% to 21%, prosthetic knees: 91% to 36%). This study demonstrated how the management of patients with suspected cases of septic arthritis of the knee may be compromised by empirical administration of antibiotics. These patients were significantly less likely to demonstrate an organism on microscopy and culture of their initial aspirate. There is a significant high false negative rate associated with knee aspiration with prior administration of antibiotic therapy.

Secondary Complete Cytoreduction in Recurrent Ovarian Cancer: Benefit of Optimal Patient Selection Using Scoring System

2014 ◽  
Vol 24 (2) ◽  
pp. 238-246 ◽  
Author(s):  
Enora Laas ◽  
Mathieu Luyckx ◽  
Marjolein De Cuypere ◽  
Frederic Selle ◽  
Emile Daraï ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Patient Selection ◽  
Positive Impact ◽  
False Negative ◽  
False Negative Rate ◽  
Recurrent Ovarian Cancer ◽  
Complete Resection ◽  
Predictive Values ◽  
Independent Population ◽  
The Impact

ObjectiveComplete tumor cytoreduction seems to be beneficial for patients with recurrent epithelial ovarian cancer (REOC). The challenge is to identify patients eligible for such surgery. Several scores based on simple clinical parameters have attempted to predict resectability and help in patient selection for surgery in REOC.The aims of this study were to assess the performance of these models in an independent population and to evaluate the impact of complete resection.Materials and MethodsA total of 194 patients with REOC between January 2000 and December 2010 were included in 2 French centers. Two scores were used: the AGO DESKTOP OVAR trial score and a score from Tian et al.The performance (sensitivity, specificity, and predictive values) of these scores was evaluated in our population. Survival curves were constructed to evaluate the survival impact of surgery on recurrence.ResultsPositive predictive values for complete resection were 80.6% and 74.0% for the DESKTOP trial score and the Tian score, respectively. The false-negative rate was high for both models (65.4% and 71.4%, respectively). We found a significantly higher survival in the patients with complete resection (59.4 vs 17.9 months,P< 0.01) even after adjustment for the confounding variables (hazard ratio [HR], 2.53; 95% confidence interval, 1.01–6.3;P= 0.04).ConclusionsIn REOC, surgery seems to have a positive impact on survival, if complete surgery can be achieved. However, factors predicting complete resection are not yet clearly defined. Recurrence-free interval and initial resection seem to be the most relevant factors. Laparoscopic evaluation could help to clarify the indications for surgery.

scholarly journals Impact of COVID-19 Lockdown on the Fisheries Sector: A Case Study from Three Harbors in Western India

2021 ◽  
Vol 13 (2) ◽  
pp. 183
Author(s):  
Ram Avtar ◽  
Deepak Singh ◽  
Deha Agus Umarhadi ◽  
Ali P. Yunus ◽  
Prakhar Misra ◽  
...  
Keyword(s):  
Global Economy ◽  
Emergency Situation ◽  
Support Vector ◽  
Small Scale ◽  
Western India ◽  
Western Coast ◽  
Land Area ◽  
Fishing Activity ◽  
South West Monsoon ◽  
The Impact

The COVID-19 related lockdowns have brought the planet to a standstill. It has severely shrunk the global economy in the year 2020, including India. The blue economy and especially the small-scale fisheries sector in India have dwindled due to disruptions in the fish catch, market, and supply chain. This research presents the applicability of satellite data to monitor the impact of COVID-19 related lockdown on the Indian fisheries sector. Three harbors namely Mangrol, Veraval, and Vankbara situated on the north-western coast of India were selected in this study based on characteristics like harbor’s age, administrative control, and availability of cloud-free satellite images. To analyze the impact of COVID in the fisheries sector, we utilized high-resolution PlanetScope data for monitoring and comparison of “area under fishing boats” during the pre-lockdown, lockdown, and post-lockdown phases. A support vector machine (SVM) classification algorithm was used to identify the area under the boats. The classification results were complemented with socio-economic data and ground-level information for understanding the impact of the pandemic on the three sites. During the peak of the lockdown, it was found that the “area under fishing boats” near the docks and those parked on the land area increased by 483%, 189%, and 826% at Mangrol, Veraval, and Vanakbara harbor, respectively. After phase-I of lockdown, the number of parked vessels decreased, yet those already moved out to the land area were not returned until the south-west monsoon was over. A quarter of the annual production is estimated to be lost at the three harbors due to lockdown. Our last observation (September 2020) result shows that regular fishing activity has already been re-established in all three locations. PlanetScope data with daily revisit time has a higher potential to be used in the future and can help policymakers in making informed decisions vis-à-vis the fishing industry during an emergency situation like COVID-19.

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