Reading up books: Computer-aided circuit analysis and design: A discussion of the role of the digital computer in circuit analysis and design is followed by a review of current literature

1984 ◽  
Vol 3 (1) ◽  
pp. 29-31
Author(s):  
George W. Zobrist
1978 ◽  
Vol 15 (3) ◽  
pp. 267-275
Author(s):  
D. B. S. J. Prasada Rao ◽  
B. P. Singh

A unified approach to transistor, F.E.T. and passive circuit analysis using the indefinite admittance matrix is presented in this paper. The indefinite admittance matrix with its easy adaptability for computer-aided analysis and design makes it a suitable basis for teaching active and passive networks.


1989 ◽  
Vol 24 (1) ◽  
pp. 128-138 ◽  
Author(s):  
J.W. Roberts ◽  
S.G. Chamberlain

2020 ◽  
Vol 26 ◽  
Author(s):  
Areti Sofogianni ◽  
Konstantinos Tziomalos ◽  
Triantafyllia Koletsa ◽  
Apostolos G. Pitoulias ◽  
Lemonia Skoura ◽  
...  

: Carotid atherosclerosis is responsible for a great proportion of ischemic strokes. Early identification of unstable or vulnerable carotid plaques and therefore of patients at high risk for stroke is of significant medical and socioeconomical value. We reviewed the current literature and discuss the potential role of the most important serum biomarkers in identifying patients with carotid atherosclerosis who are at high risk for atheroembolic stroke.


2021 ◽  
Vol 14 ◽  
pp. 263177452199305
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Zhongheng Zhang ◽  
...  

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.


Author(s):  
C. Galup-Montoro ◽  
M. C. Schneider ◽  
A. I. A. Cunha ◽  
F. Rangel de Sousa ◽  
Hamilton Klimach ◽  
...  

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