Utilization of Percutaneous Needle Biopsy for Breast Diagnosis in a Comprehensive Breast Center: Implications for Development of Quality Indicators

Holloway, Claire; Alriyees, L; Saskin, Refik

doi:10.1007/s00268-015-3293-0

“…The above formula represents the weighted sum of unit inputs. Backpropagation is based on the chain rule to derivate from back to front, and finally find the residual value of all neural network nodes [28][29][30][31].…”

Section: Fig 3 Schematic Diagram Of Convolution Operation and Transposed Convolution Operationmentioning

confidence: 99%

Design of intelligent diagnosis system for teaching quality based on wireless sensor network and data mining

Zhang

¹

,

Huang

²

2021

J Wireless Com Network

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With the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.

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“…8Simply replace the relationship with (9): (9) The above formula represents the weighted sum of unit inputs. Backpropagation is based on the chain rule to derivate from back to front, and finally find the residual value of all neural network nodes [30]. (10) With the formula for calculating the residuals of each node of the neural network, the weight parameters and partial derivatives of the neural network loss function can be calculated separately.…”

Section: Figure 3 Schematic Diagram Of Convolution Operation and Tranmentioning

confidence: 99%

Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

Zhang

¹

,

Huang

²

2020

Preprint

1

0

View full text Add to dashboard Cite

With the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.

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“…1 Early diagnosis of breast cancer in young women may be challenging because of common benign breast diseases and dense breast tissue on clinical breast exam and imaging. 1,2 Although percutaneous core needle biopsy (PNB) has become the accepted diagnostic tool after imaging for breast pathology and use of PNB has been proposed as a quality measure for breast cancer care, 3,4 this minimally invasive procedure has not been well studied in young women. We sought to determine the effectiveness and necessity of PNB in patients younger than 35 years.…”

mentioning

confidence: 99%

Percutaneous Needle Biopsies of the Breast in Women Younger than 35 Years: Minimally or Excessively Invasive?

Abou-zamzam

¹

,

Somers

²

,

Cora

³

et al. 2017

The American Surgeon™

2

0

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Percutaneous needle biopsy (PNB) of the breast is commonly used for diagnosis of breast pathology, but has been less studied in young women. We sought to determine the effectiveness and necessity of PNB in patients younger than 35 years of age. The charts of sequential patients <35 years who underwent PNB between February 2013 and May 2016 were reviewed; 181 PNB were performed in 127 patients. Median age was 30 years (13–34). Indications for PNB were Breast Imaging Reporting and Data System (BIRADS) ≥4 in 137 (75.7%) cases, with mass on imaging in 139 (76.8%). Carcinoma was diagnosed in 12 (6.6%), PNB in eight unique patients (6.3%). Other PNB pathology included atypia in four (2.2%) patients; papillary lesion, five (2.8%); benign lymph node, 10 (5.5%); fibroepithelial lesion, 15 (8.3%); benign breast tissue, 63 (34.8%); and fibroadenoma, 72 (39.8%). Women with atypia or malignancy were older than those with benign findings (30.9 vs 28.0 years, P = 0.002). No other patient or imaging factors were significantly associated with pathologic diagnosis on PNB. Routine PNB for all BIRADS 4 findings may be over-used in young women as most results are benign and subsequent surgical findings are concordant. Improved diagnostic accuracy of breast imaging is warranted to reduce unnecessary procedures.

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Utilization of Percutaneous Needle Biopsy for Breast Diagnosis in a Comprehensive Breast Center: Implications for Development of Quality Indicators

Abstract: The vast majority of lesions requiring tissue diagnosis can be accurately diagnosed with PNB. Benchmarks for rates of PNB of 90 % or greater may be considered for performance measurement in appropriate populations.

Cited by 3 publications

References 23 publications

Design of intelligent diagnosis system for teaching quality based on wireless sensor network and data mining

Design of intelligent diagnosis system for teaching quality based on wireless sensor network and data mining

Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

Percutaneous Needle Biopsies of the Breast in Women Younger than 35 Years: Minimally or Excessively Invasive?

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