Feasibility of FT-NIR spectroscopy and Vis/NIR hyperspectral imaging for sorting unsound chestnuts

Authors explored the potential use of Vis/NIR hyperspectral imaging (HSI) and Fourier-transform Near-Infrared (FT-NIR) spectroscopy to be used as in-line tools for the detection of unsound chestnut fruits (i.e. infected and/or infested) in comparison with the traditional sorting technique. For the intended purpose, a total of 720 raw fruits were collected from a local company. Chestnut fruits were preliminarily classified into sound (360 fruits) and unsound (360 fruits) batches using a proprietary floating system at the facility along with manual selection performed by expert workers. The two batches were stored at 4 ± 1 °C until use. Samples were left at ambient temperature for at least 12 h before measurements. Subsequently, fruits were subjected to non-destructive measurements (i.e. spectral analysis) immediately followed by destructive analyses (i.e. microbiological and entomological assays). Classification models were trained using the Partial Least Squares Discriminant Analysis (PLS-DA) by pairing the spectrum of each fruit with the categorical information obtained from its destructive assay (i.e., sound, Y = 0; unsound, Y = 1). Categorical data were also used to evaluate the classification performance of the traditional sorting method. The performance of each PLS-DA model was evaluated in terms of false positive error (FP), false negative error (FN) and total error (TE) rates. The best result (8% FP, 14% FN, 11% TE) was obtained using Savitzky-Golay first derivative with a 5-points window of smoothing on the dataset of raw reflectance spectra scanned from the hilum side of fruit using the Vis/NIR HSI setup. This model showed similarity in terms of False Negative error rate with the best one computed using data from the FT-NIR setup (i.e. 15% FN), which, however, had the lowest global performance (17% TE) due to the highest False Positive error rate (19%). Finally, considering that the total error rate committed by the traditional sorting system was about 14.5% with a tendency of misclassifying unsound fruits, the results indicate the feasibility of a rapid, in-line detection system based on spectroscopic measurements.

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Error Rates in Competency Testing When Test Retaking Is Permitted

Journal of Educational Statistics ◽

10.3102/10769986015001039 ◽

1990 ◽

Vol 15 (1) ◽

pp. 39-52 ◽

Cited By ~ 1

Author(s):

Huynh Huynh

Keyword(s):

Conditional Probability ◽

False Positive ◽

False Negative ◽

Error Rates ◽

Rasch Models ◽

Positive Error ◽

False Positive Error ◽

Competency Testing ◽

Negative Error ◽

False Negative Error

False positive and false negative error rates are studied for competency testing where examinees are permitted to retake the test if they fail to pass. Formulae are provided for the beta-binomial and Rasch models, and estimates based on these two models are compared for several typical situations. Although Rasch estimates are expected to be more accurate than beta-binomial estimates, differences among them are found not to be substantial in a number of practical situations. Under relatively general conditions and when test retaking is permitted, the probability of making a false negative error is zero. Under the same situation, and given that an examinee is a true nonmaster, the conditional probability of making a false positive error for this examinee is one.

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Errors in prostate core biopsy diagnosis in an era of specialisation and double reporting

Journal of Clinical Pathology ◽

10.1136/jclinpath-2020-206726 ◽

2020 ◽

pp. jclinpath-2020-206726

Author(s):

Cornelia Margaret Szecsei ◽

Jon D Oxley

Keyword(s):

Error Rate ◽

False Positive ◽

Core Biopsy ◽

False Negative ◽

Diagnostic Error ◽

Error Rates ◽

False Positive Error ◽

Biopsy Diagnosis ◽

False Negative Error ◽

False Positive Error Rate

AimTo examine the effects of specialist reporting on error rates in prostate core biopsy diagnosis.MethodBiopsies were reported by eight specialist uropathologists over 3 years. New cancer diagnoses were double-reported and all biopsies were reviewed for the multidisciplinary team (MDT) meeting. Diagnostic alterations were recorded in supplementary reports and error rates were compared with a decade previously.Results2600 biopsies were reported. 64.1% contained adenocarcinoma, a 19.7% increase. The false-positive error rate had reduced from 0.4% to 0.06%. The false-negative error rate had increased from 1.5% to 1.8%, but represented fewer absolute errors due to increased cancer incidence.ConclusionsSpecialisation and double-reporting have reduced false-positive errors. MDT review of negative cores continues to identify a very low number of false-negative errors. Our data represents a ‘gold standard’ for prostate biopsy diagnostic error rates. Increased use of MRI-targeted biopsies may alter error rates and their future clinical significance.

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Evaluation of the European Fish Index: false-positive and false-negative error rate to detect disturbance and consistency with alternative fish indices

Fisheries Management and Ecology ◽

10.1111/j.1365-2400.2007.00573.x ◽

2007 ◽

Vol 14 (6) ◽

pp. 465-472 ◽

Cited By ~ 5

Author(s):

P. QUATAERT ◽

J. BREINE ◽

I. SIMOENS

Keyword(s):

Error Rate ◽

False Positive ◽

False Negative ◽

Negative Error ◽

False Negative Error ◽

Fish Index

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Response Error and the Medicaid Undercount in the Current Population Survey

10.31235/osf.io/ch8qt ◽

2017 ◽

Author(s):

James Noon ◽

Leticia Fernandez ◽

Sonya Rastogi

Keyword(s):

False Positive ◽

Current Population Survey ◽

Population Survey ◽

False Negative ◽

Positive Error ◽

False Positive Error ◽

Response Error ◽

Medicaid Enrollment ◽

False Negative Error ◽

Uninsured Population

The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) is an important source for estimates of the uninsured population. Previous research has shown that survey estimates produce an undercount of beneficiaries compared to Medicaid enrollment records. We extend past work by examining the Medicaid undercount in the 2007-2011 CPS ASEC compared to enrollment data from the Medicaid Statistical Information System for calendar years 2006-2010. By linking individuals across datasets, we analyze two types of response error regarding Medicaid enrollment – false negative error and false positive error. We use regression analysis to identify factors associated with these two types of response error in the 2011 CPS ASEC. We find that the Medicaid undercount was between 22 and 31 percent from 2007 to 2011. In 2011, the false negative rate was 40 percent, and 27 percent of Medicaid reports in CPS ASEC were false positives. False negative error is associated with the duration of enrollment in Medicaid, enrollment in Medicare and private insurance, and Medicaid enrollment in the survey year. False positive error is associated with enrollment in Medicare and shared Medicaid coverage in the household. We discuss implications for survey reports of health insurance coverage and for estimating the uninsured population.

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Sample size determination for comparing two therapies taking both the α (type I or false positive) error and the β (type II or false negative) error into consideration

Applied Mathematics and Computation ◽

10.1016/0096-3003(77)90028-5 ◽

1977 ◽

Vol 3 (2) ◽

pp. 169-174

Author(s):

Vrudhula K. Murthy ◽

L.Julian Haywood

Keyword(s):

Sample Size ◽

False Positive ◽

False Negative ◽

Sample Size Determination ◽

Type I ◽

Type Ii ◽

Size Determination ◽

Positive Error ◽

False Positive Error ◽

False Negative Error

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A Study of False-Positive and False-Negative Error Rates in Cartridge Case Comparisons

10.21236/ada611807 ◽

2014 ◽

Cited By ~ 2

Author(s):

David P. Baldwin ◽

Stanley J. Bajic ◽

Max Morris ◽

Daniel Zamzow

Keyword(s):

False Positive ◽

False Negative ◽

Error Rates ◽

Negative Error ◽

False Negative Error ◽

Cartridge Case

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“Missed” Mild Cognitive Impairment: High False-Negative Error Rate Based on Conventional Diagnostic Criteria

Journal of Alzheimer s Disease ◽

10.3233/jad-150986 ◽

2016 ◽

Vol 52 (2) ◽

pp. 685-691 ◽

Cited By ~ 37

Author(s):

Emily C. Edmonds ◽

Lisa Delano-Wood ◽

Amy J. Jak ◽

Douglas R. Galasko ◽

David P. Salmon ◽

...

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Diagnostic Criteria ◽

Error Rate ◽

False Negative ◽

Negative Error ◽

False Negative Error

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High resolution analysis of cervical cells--a progress report.

Journal of Histochemistry & Cytochemistry ◽

10.1177/25.7.330722 ◽

1977 ◽

Vol 25 (7) ◽

pp. 689-695 ◽

Cited By ~ 11

Author(s):

R S Poulsen ◽

L H Oliver ◽

R L Cahn ◽

C Louis ◽

G Toussaint

Keyword(s):

High Resolution ◽

False Positive ◽

False Negative ◽

Error Rates ◽

Cell Segmentation ◽

Negative Error ◽

False Negative Error ◽

High Resolution Analysis ◽

Resolution Analysis ◽

Cervical Cells

This paper presents preliminary results of research toward the development of a high resolution analysis stage for a dual resolution image processing-based prescreening device for cervical cytology. Experiments using both manual and automatic methods for cell segmentation are described. In both cases, 1500 cervical cells were analyzed and classified as normal or abnormal (dysplastic or malignant) using a minimum Mahalanobis distance classifier with eight subclasses of normal cells, and five subclasses of abnormal cells. With manual segmentation, false positive and false negative error rates of 2.98 and 7.73% were obtained. Similar experiments using automatic cell segmentation methods yielded false positive and false negative error rates of 3.90 and 11.56%, respectively. In both cases, independent training and testing data were used.

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