scholarly journals Classification of Cancer of The Lungs Using SVM and ANN

2015 ◽  
Vol 15 (1) ◽  
pp. 6418-6426 ◽  
Author(s):  
Olusayo Deborah Fenwa ◽  
Funmilola A. Ajala ◽  
Adebisi A. Adigun
Keyword(s):  
Lung Diseases ◽  
Human Life ◽  
False Negative ◽  
Accurate Diagnosis ◽  
Lung Nodules ◽  
True Positive ◽  
True Negative ◽  
Diagnosis Of Cancer ◽  
Sensitivity Specificity

Accurate diagnosis of cancer plays an important role in order to save human life. The results of the diagnosis indicate by the medical experts are mostly differentiated based on the experience of different medical experts. This problem could risk the life of the cancer patients. A fast and effective method to detect the lung nodules and separate the cancer images from other lung diseases like tuberculosis is becoming increasingly needed due to the fact that the incidence of lung cancer has risen dramatically in recent years and an early detection can save thousands of lives each year. The focus of this paper is to compare the performance of the ANN and SVM classifiers on acquired online cancer datasets. The performance of both classifiers is evaluated using different measuring parameters namely; accuracy, sensitivity, specificity, true positive, true negative, false positive and false negative.

scholarly journals Comparison of diagnostic accuracy of papanicoloau (PAP) Smear and visual inspection using acetic acid (VIA) in screening of cervical carcinoma, taking biopsy as gold standard.

2020 ◽  
Vol 27 (04) ◽  
pp. 863-869
Author(s):  
Shakila Yasmin ◽  
Tahira Munir ◽  
Ayesha Javaid ◽  
Khalid Fahim Yasin ◽  
Junaid Hassan
Keyword(s):  
Acetic Acid ◽  
Diagnostic Accuracy ◽  
Cervical Carcinoma ◽  
Predictive Value ◽  
Visual Inspection ◽  
Pap Smear ◽  
False Negative ◽  
True Positive ◽  
True Negative ◽  
Sensitivity Specificity

Study Design: Cross-sectional descriptive study. Setting: Department of Obstetrics & Gynecology, Bahawal Victoria Hospital, Bahawalpur. Period: 05 August 2016 to 05 Feb 2017. Material & Methods: A total of 228 suspected patients of cervical carcinoma and age of 20-50 years were included. Patients with acute cervicitis, pregnant females, h/o abnormal cytology and obvious lesion on cervix were excluded. All the patients were underwent papanicoloau (PAP) smear and visual inspection using acetic acid. The results of papanicoloau (PAP) smear and visual inspection using acetic acid (VIA) were compared with cervical biopsy report. Results: In 110 papanicoloau (PAP) smear positive patients, 97 were True Positive and 13 were False Positive. Among, 118 papanicoloau (PAP) smear negative patients, 18 were False Negative whereas 100 were True Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of papanicoloau ( PAP )smear in screening of cervical carcinoma was 84.35%, 88.50%, 88.18%, 84.75% and 86.40% respectively. In 114 visual inspection using acetic acid (VIA) positive patients, 95 were True Positive and 19 were False Positive. Among, 114 visual inspection using acetic acid (VIA) negative patients, 20 were False Negative whereas 94 were True Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of visual inspection using acetic acid ( VIA) in  screening of cervical carcinoma was 82.61%, 83.19%, 83.33% 82.46% and 82.89% respectively. Conclusion: This study concluded that papanicoloau ( PAP) smear and visual inspection using acetic acid (VIA) in screening of cervical carcinoma are highly sensitive, accurate and having almost equal diagnostic accuracy.

The Clinically Relevant Breast Imaging Audit

2020 ◽  
Vol 2 (1) ◽  
pp. 2-6
Author(s):  
Carl Joseph D’Orsi
Keyword(s):  
Breast Imaging ◽  
False Negative ◽  
Accurate Method ◽  
Recall Rate ◽  
Basic Data ◽  
True Positive ◽  
True Negative ◽  
Data Points ◽  
Diagnosis Of Cancer ◽  
Definition Of

Abstract An audit of a breast imaging practice must be based on data with accepted definitions and rules so that the comparisons between breast imaging facilities and interpretive staff are comparable. The four basic data points for calculating these metrics are true positive (TP), true negative (TN), false positive (FP), and false negative (FN). For mammography, the definition of “true” is the presence of a proven malignancy within a year of the exam. The presence or absence of breast cancer within a year of the exam and an increase in patient mobility between different facilities may render the calculation of sensitivity and specificity difficult for most facilities unless a regional cancer registry is available.Thus, the metrics that can be easily calculated within a facility are recall rate (all the positive interpretations divided by all the exams read), positive predictive value (PPV) 1 = percentage of abnormal screening exams that result in a diagnosis of cancer within a year, PPV2 = percentage of all diagnostic exams recommended for biopsy and cancer discovered within a year, PPV3 = benign tissue diagnosis and no cancer within a year, and the cancer detection rate (the true positive exams per one thousand exams). Intuitively, one may assume that accuracy (TP + TN/TP + FP + TN + FN) is the best metric for an interpreter. However, this can produce spurious results. The most accurate method to determine a reader’s skills is the use of the receiver operating characteristic (ROC) curve, which clearly presents, in graphic form, the relationship between the four basic data points.

scholarly journals Classification of Melanoma and Nevus for Diagnosis of Skin Cancer by Using Optimized Convolution Neural Network

2021 ◽  
Vol 9 (12) ◽  
pp. 1984-1989
Author(s):  
Neha Maheshwari
Keyword(s):  
Neural Network ◽  
Median Filter ◽  
Confusion Matrix ◽  
False Negative ◽  
Convolution Neural Network ◽  
True Positive ◽  
True Negative ◽  
Index Terms ◽  
Risk Of Cancer

Abstract: Melanoma is taken into account a fatal sort of carcinoma .Differentiating melanoma from nevus is difficult task. Nevus is a common pigmented skin lesion, usually developing during adulthood, which is harmless. Since they look similar it has to be identified and reduce the risk of cancer. The death rate thanks to this disease is in particular other skin-related consolidated malignancies. In this work, we have used convolution neural networks to classify the image into melanoma and nevus. The images are pre-processed using median filter, top-bottom hat filter and are passed through layers of CNN. We have achieved an accuracy of 97.56%, sensitivity of 95.23%.The F1_socre is 97.56. Index terms: Melanoma, Nevus, True Positive, True Negative, False Negative, False Positive, Confusion Matrix, Epoch, Convolution Neural Network.

scholarly journals Limited Positive Predictive Value of β-d-Glucan in Hematologic Patients Receiving Antimold Prophylaxis

2020 ◽  
Vol 7 (3) ◽  
Author(s):  
Euijin Chang ◽  
Taek Soo Kim ◽  
Chang Kyung Kang ◽  
Kang Il Jun ◽  
Dongyeop Shin ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
False Negative ◽  
Diagnostic Value ◽  
Tertiary Hospital ◽  
True Positive ◽  
True Negative ◽  
Cell Transplants ◽  
Sensitivity Specificity ◽  
Low Prevalence

Abstract Background Diagnostic value of β-d-glucan (BDG) in populations with low prevalence of invasive fungal infection (IFI), such as hematologic patients receiving antimold prophylaxis, should be re-evaluated. Methods We retrospectively reviewed episodes with BDG results in hematologic patients receiving antimold prophylaxis from January 2017 to August 2019 in a tertiary hospital. The episodes were classified as true positive ([TP] positive BDG with IFI), true negative ([TN] negative BDG without IFI), false positive ([FP] positive BDG without IFI), false negative ([FN] negative BDG with IFI), and nonevaluable. Results A total of 203 episodes were analyzed: 101 episodes (49.8%) were from stem cell transplants, 89 (43.8%) were from induction chemotherapy, and 13 (6.4%) were from graft-versus-host disease treatment. There were 62 nonevaluable episodes. Among 141 evaluable ones, there were 8 (5.7%) episodes of probable/proven IFI. True positive, TN, FP, and FN cases were 4 (2.8%), 112 (79.4%), 21 (14.9%), and 4 (2.8%) episodes, respectively. Sensitivity, specificity, positive predictive value, and negative predictive value were 50.0%, 84.2%, 16.1%, and 96.5%, respectively. Positive predictive value was 26.7% and 0.0% in diagnostic and surveillance episodes, respectively. Conclusions β-d-glucan test should be used to exclude IFI rather than for diagnosis in these patients.

PS02.079: ESOPHAGEAL ADENOCARCINOMA: CT, PET, EUS SENSITIVITY/SPECIFICITY FOR THE PREOPERATIVE ASSESSMENT OF LYMPH NODE METASTASES IN SINGLE THORACIC AND ABDOMINAL NODAL STATIONS

2018 ◽  
Vol 31 (Supplement_1) ◽  
pp. 142-143
Author(s):  
Juha Kauppi ◽  
Marialuisa Lugaresi ◽  
Egesta Lopci ◽  
Niccolò Daddi ◽  
Jari Räsänen ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Nodes ◽  
Esophageal Adenocarcinoma ◽  
Preoperative Staging ◽  
False Negative ◽  
Clinical Staging ◽  
Lymph Node Status ◽  
True Positive ◽  
True Negative ◽  
Sensitivity Specificity

Abstract Background In esophageal adenocarcinoma clinical staging (cStaging), interest for N-descriptor according to single lymph nodal station has emerged, but no specific data are available. CT, PET, EUS sensitivity/specificity for N-descriptor in single stations were investigated. Methods In 101 esophageal adenocarcinoma cases (60/41 Siewert I/II) preoperative staging and primary radical surgical resection (prospective protocols) were performed. Resected lymphatic nodes (LNY) and lymphatic metastases (LNM) were reported for the following stations: A) right paratracheal/sub carinal/pulmonary ligament; B) paraesophageal thoracic; C) pericardial; D) left gastric artery, lesser curvature; E) celiac trunk, hepatic/splenic artery. Pathological N data were compared with clinical N-descriptors. Results LN stations: A) LNY 137 LNM 6, Sensitivity CT 58.3%, PET 7.1%, EUS 87.5%—Specificity CT 94.3%, PET 98.8%, EUS 88.6%; B) LNY 79 LNM 18, Sensitivity CT 33.3%, PET 20%, EUS 80%—Specificity CT 92.1%, PET 96.6%, EUS 87.2%; C) LNY189 LNM 36, Sensitivity CT 46.6%, PET 23.5%, EUS 28.5%—Specificity CT 95.3%, PET 97.5%, EUS 97.7%; D) LNY 383 LNM 66, Sensitivity CT 24.1%, PET 21.4%, EUS 33.3%—Specificity CT 97.2%, PET 97.2%, EUS 100%; E) LNY 148 LNM 17, Sensitivity CT 13.3%, PET 5.5%, EUS 33.3%—Specificity CT 93%, PET 98.7%, EUS 95.2%. Figure Staging in adenocarcinoma of the esophageal-gastric junction; CT (A), PET (B) and fused PET/CT sessions (C) at the level of the primary tumor (red arrows) and para-esophageal lymph nodes including one PET-positive (red arrowheads), and one PET-negative detectable on CT only (yellow arrowheads). Panel D the box-plot for median SUVmax according to pathologic lymph node status. In the true positive lymph nodes, SUVmax was significantly higher than in true negative (median, 13.6 vs 5.0, P = 0.001) and false negative lymph nodes (median, 13.6 vs 6.9; P = 0.026). Abbreviations: FN = false negative; TP = true positive; TN = true negative. Conclusion For esophageal adenocarcinoma cStaging, CT, PET, EUS N-descriptor is not reliable, particularly PET data for N stations close to primary T. To tailor therapy, new biological descriptors are necessary. Disclosure All authors have declared no conflicts of interest.

scholarly journals Comparison of Ultrasonography and Fine Needle Aspiration Cytology in the Diagnosis of Malignant Breast Lesions in a Rural Setup

2016 ◽  
Vol 02 (02) ◽  
pp. 058-065
Author(s):  
Rounak Kalwani ◽  
K Kher ◽  
Sonam Daftari
Keyword(s):  
False Negative ◽  
Needle Aspiration ◽  
True Positive ◽  
Breast Lump ◽  
Aspiration Cytology ◽  
True Negative ◽  
Predictive Values ◽  
Malignant Breast ◽  
Needle Aspiration Cytology ◽  
Sensitivity Specificity

Abstract Introduction: Breast cancer is the most common cancer diagnosed in women worldwide. These rising trends have emphasized the need of prompt detection, effective clinical evaluation, and exact diagnosis of the breast disease. Aim: To analyze and compare the sensitivity, specificity, and predictive values and accuracy of ultrasonography (USG) and fine needle aspiration cytology (FNAC) in diagnosing malignant breast lump. Materials and methods: A cross-sectional, prospective study was done. One hundred sixteen female patients attending surgery department with breast lump were included. After complete clinical evaluation of the lump, all patients underwent USG and FNAC examination for diagnosis of the lump, and further subjected to excisional biopsy/definitive surgery, the results of which were further compared with the histopathological results to determine the accuracy, sensitivity, specificity, and predictive values of FNAC and USG. Results: Out of 116, 61 (52.58%) benign lesions were found while the remaining 55 (47.41%) resulted to be malignant lesions on histopathological examination (HPE). Ultrasonography reported 46 true positive, 60 true negative, and 4 false negative cases with 6 inconclusive reports; whereas, FNAC reported 47 true positive, 61 true negative, and 6 false negative cases with 2 inconclusive reports. There were no false positive cases detected by USG and FNAC. Thus, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for USG was found to be 92, 100, 100, 93.75, and 96.36% (χ2-value = 94.88, p-value = 0.0001,S) and values of 88.68, 100, 100, 91.04, and 94.73% were obtained for FNAC respectively (χ2-value = 92.04, p = 0.0001,S). Conclusion: In diagnosing malignant breast lesion, USG and FNAC are 100% specific. Although USG appears more sensitive than FNAC, the percentage of indeterminate report is higher with USG.

The role of serum periostin in the diagnosis of asthma: A meta-analysis

2020 ◽  
Vol 41 (4) ◽  
pp. 240-247
Author(s):  
Lei Yang ◽  
Qingtao Zhao ◽  
Shuyu Wang
Keyword(s):  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Summary Receiver Operating Characteristic ◽  
True Negative ◽  
Negative Results ◽  
Noninvasive Biomarker ◽  
Sensitivity Specificity ◽  
Serum Periostin

Background: Serum periostin has been proposed as a noninvasive biomarker for asthma diagnosis and management. However, its accuracy for the diagnosis of asthma in different populations is not completely clear. Methods: This meta-analysis aimed to evaluate the diagnostic accuracy of periostin level in the clinical determination of asthma. Several medical literature data bases were searched for relevant studies through December 1, 2019. The numbers of patients with true-positive, false-positive, false-negative, and true-negative results for the periostin level were extracted from each individual study. We assessed the risk of bias by using Quality Assessment of Diagnostic Accuracy Studies 2. We used the meta-analysis to produce summary estimates of accuracy. Results: In total, nine studies with 1757 subjects met the inclusion criteria. The pooled estimates of sensitivity, specificity, and diagnostic odds ratios for the detection of asthma were 0.58 (95% confidence interval [CI], 0.38‐0.76), 0.86 (95% CI, 0.74‐0.93), and 8.28 (95% CI, 3.67‐18.68), respectively. The area under the summary receiver operating characteristic curve was 0.82 (95% CI, 0.79‐0.85). And significant publication bias was found in this meta‐analysis (p = 0.39). Conclusion: Serum periostin may be used for the diagnosis of asthma, with moderate diagnostic accuracy.

scholarly journals Coupling Uncertainties with Accuracy Assessment in Object-based Slum Detections, Case Study: Jakarta, Indonesia

2017 ◽  
Author(s):  
Jati Pratomo ◽  
Monika Kuffer ◽  
Javier Martinez ◽  
Divyani Kohli
Keyword(s):  
Land Tenure ◽  
Classification Accuracy ◽  
Accuracy Assessment ◽  
False Negative ◽  
National Policy ◽  
True Positive ◽  
True Negative ◽  
Object Based ◽  
The Impact

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

scholarly journals Comparison Study Between Local TSH IRMA Kit (CRRT) and Imported TSH IRMA Kit (Riakey, Korea)

2019 ◽  
Vol 4 (2) ◽  
pp. 77
Author(s):  
Gina Mondrida ◽  
Triningsih Triningsih ◽  
Kristina Dwi Purwanti ◽  
Sutari Sutari ◽  
Sri Setyowati ◽  
...  
Keyword(s):  
False Negative ◽  
Thyroid Stimulating Hormone ◽  
The Body ◽  
True Positive ◽  
Comparison Study ◽  
Complex Matrix ◽  
Normal Range ◽  
True Negative ◽  
Immunoassay Technique ◽  
Tsh Levels

<p><em>Thyroid Stimulating Hormone</em> (TSH) is one of hormones that our body need for growth of brains, bones and other tissues and regulate the metabolism in the body. Normal range of TSH for adult is from 0.3 to 5.5 µIU/ml, whereas for baby ranged from 3 to 18 µIU/ml. An Immunoradiometricassay (IRMA) is one of immunoassay technique using radionuclide as the tracer to detect low quantity of analyte. This technique is suitable for determine TSH levels in human blood serum which has complex matrix and various concentration. The Center for Radioisotope and Radiopharmaceutical Technology (CRRT)-BATAN has developed a reagent of TSH IRMA kit. The aim of this research is to compare between local TSH IRMA kit (CRRT-BATAN) and imported TSH IRMA kit (Riakey, Korea) toward 110 adult samples obtained from PTKMR - BATAN. The results showed 97 samples as true negative, 5 samples as true positive, 1 sample as false negative and 7 samples false positive. The comparison study gave diagnostic sensitivity as much as 83.33 %, diagnostic spesificity as much as 93.27 % and accuracy as much as 92.72 %.</p>

scholarly journals Discordance between fine-needle aspiration cytology and histopathology in patients with mucoepidermoid carcinoma of parotid gland

2020 ◽  
Vol 102 (5) ◽  
pp. 340-342
Author(s):  
H Iftikhar ◽  
M Sohail Awan ◽  
M Usman ◽  
A Khoja ◽  
W Khan
Keyword(s):  
Fine Needle Aspiration ◽  
Fine Needle Aspiration Cytology ◽  
Mucoepidermoid Carcinoma ◽  
False Negative ◽  
Needle Aspiration ◽  
True Positive ◽  
Aspiration Cytology ◽  
True Negative ◽  
Fine Needle ◽  
Needle Aspiration Cytology

Introduction Fine-needle aspiration cytology (FNAC) is an important diagnostic tool used preoperatively for the diagnosis of parotid lump. Mucoepidermoid carcinoma comprises 5–10% of all salivary gland tumours. It poses a diagnostic challenge on FNAC with high false negative rate. The objective of this study was to evaluate the discordance between cytology/FNAC and histopathology in patients with mucoepidermoid carcinoma. Material and methods A cross-sectional study was conducted from 1 January 2010 to 31 December 2014. Patients aged 18 years and above with FNAC or histopathology suggestive of mucoepidermoid carcinoma were identified. FNAC when compared with histology (gold standard) was classified into true positive (presence of mucoepidermoid carcinoma correctly diagnosed on FNAC), true negative (absence of mucoepidermoid carcinoma correctly diagnosed on FNAC), false positive (FNAC incorrectly diagnosed mucoepidermoid carcinoma), false negative (FNAC failed to diagnose mucoepidermoid carcinoma). Results A total of 16 patients fulfilled our eligibility criteria. Seven cytological samples were true positive (ie correctly diagnosed mucoepidermoid carcinoma by FNAC), eight cytological specimens were false negative (ie could not pick up mucoepidermoid carcinoma on FNAC). One case was false positive on cytology (ie diagnosed mucoepidermoid carcinoma on FNAC but was reported to be Warthin’s tumour on histopathology) and none were true negative. Conclusion FNAC is not reliable for diagnosis of mucoepidermoid carcinoma. More than 50% of our patients had discordant results between cytology and histology. We recommend a high index of suspicion for mucoepidermoid carcinoma given the poor yield of cytology.

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